Impact of IoT Technology on the Business Performance of SMEs

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Introduction

The Internet of Things (IoT) ecosystem is comprised of web-enabled smart devices that rely on embedded subsystems and networking gears, to collect, transmit, and utilize the information gathered from their environment. Invented in 1999, consumer sensor expert Kevin Ashton was motivated by his desire to link objects in the physical world with the internet. The computer scientist proposed the installation of radio-frequency identification (RFID) chips on merchandise to follow them during the supply chain. Since then, many linked devices have entered the market due to the high interest in IoT technology. As of 2008, the number of linked devices exceeded the earth’s population at that time (Pham, 2019). Whereas consumer IoT features all wearable digital devices, commercial and public IoT entail concepts of smart factories and automated waste management systems respectively.

When connected to an IoT access point, digital devices can exchange sensor data. The former either analyses the data locally or sends it to the Cloud. Depending on the available data, these devices routinely interlink with other similar models. Although users can interact with the devices to power, program, and retrieve data from them, the majority of their functions are accomplished on autopilot. The specific IoT tasks that these digital technologies have been designed to perform are used to determine their accessibility, connectivity, and interface protocols. There are those which employ artificial intelligence to help make data collection processes simpler and more flexible.

Organizations may use IoT to monitor how their systems work in real-time and remotely monitor different aspects of operation. Since the inception of IoT, SMEs have been able to automate procedures and minimize labour-related expenditures. Furthermore, this digital resource reduces the cost of delivering goods, lowers inefficiency, improves service delivery, and boosts consumer satisfaction (Pham, 2019). Ideally, IoT is a crucial structural component in both organisations and businesses. This explains why it is projected to gain traction as more enterprises appreciate the role played by interlinked digital devices in their daily operations.

Businesses can derive a wide range of benefits from IoT incorporation. Although some benefits are limited to large companies, most of them can be enjoyed by all firms in different industries. Common advantages of IoT include the ability for firms to monitor their entire business operations, increased employee efficiency, and easy adaptability to new business models. IoT provides businesses with the tools they need to improve their operations and further pushes them to strategize on how they can compete more effectively.

As a result, it has been identified useful for organizations within the agribusiness, manufacturing, IT, transport, and home automation industries, leading these enterprises toward digital transmutability. Additionally, IoT can be used to assist businesses that provide urban planning services. For example, sensors could be helpful when determining the structural elevation of buildings, roads, and bridges. The major advantages related to this capability include savings in cost and time while concomitantly reducing paperwork and human engagement in production.

Based on the above discussion, SMEs have been actively pursuing possibilities for profitability and expansion through the incorporation of IoT-driven operation and digital servitization competencies. The present corpus of research, however, yields considerable discrepancies in findings regarding the impact of IoT technology on digital servitization and SME performance. Additionally, a framework on how IoT product systems assist SMEs in improving their servitization efficiency and subsequently, the performance of firms and supply chains, is yet to be established and tested through extensive survey-based empirical studies.

For a long time, enterprises and organizations in the SME sector, both large and small, have prioritized digital transformation owing to the desire to survive in their respective business industries. The recent decades have experienced high interest regarding the need for cloud-based digitalization, with new product service systems emerging every day. Some businesses have gone to the extent of creating new corporate positions like the digitalization director (Sestino et al., 2020). According to 57% of small business owners, the major obstacle to achieving digital transmutability goals is the lack of adequate literature and information to support the adoption of rigorous technological solutions that are developing extremely fast. This slows down the deployment of IoT resources for firms which may be primarily focused on the uncertainties associated with this trend.

It can be overwhelming for the late adopters to make the right decision on which path would be most convenient when chosen. Early adopters, on the other hand, might remain stuck in obsolete technologies due to their uncertainties on newly invented models. Whereas the IoT incentives and key drivers can be easily accessed, SMEs are incapable of fully leveraging IoT’s potential as there are only a few clear and tested roadmaps for using IoT product systems.

This study aims at addressing the fore cited gaps by identifying ways in which IoT, servitization, and digitalization are interconnected and how the IoT can improve SMEs’ operation bottom line. It further discusses how SME owners can improve business processes through technology. The research builds and tests a paradigm for evaluating the effect of servitization and digitalization on business overall performance to fill existing literature gaps and resolve contradictory results. The relevance, inclusivity, and eligibility of secondary sources used in the literature review will be determined by the systematic review approach.

On the other hand, the methodologies used during the actual study will be obtained from the Research Onion model by Saunder et al., (2009). This study could be relevant to auditors when evaluating the financial position of a firm by assessing its aggressiveness in servitization engagement (Kohtamäki et al., 2022). Similarly, entrepreneurs who are willing and able to venture into the SME industry can use the results from this study to assess the benefits of IoT incorporation in their businesses.

Aim

This study aims at assessing the impacts of IoT incorporation by SMEs on their servitization culture, supply chain, growth, and sustainability aspects used to gauge business performance.

Objectives

This research has the following objectives:

1. To establish the impacts of IoT incorporation on the rapid innovations (attributed to digital servitization) witnessed among SMEs in the U.K.
2. To identify the impacts of IoT (attributed to digital servitization) on supply chain excellence.
3. To investigate the effect of the adoption of digital incentives pioneered by IoT on the overall growth and sustainability of SMEs.
4. To identify the effects of IoT inception on SME financial performance in different fiscal spans.

All the objectives target SMEs in the U.K., the study is time-bound (three months) and the different aspects of business performance (supply chain, rate of innovation, SMEs growth, digital servitization, and financial performance) to be explored are measurable.

Structure of the Project

Chapter 1 (the background) starts by introducing the dissertation’s outline. It gives basic information about the study followed by a quick review that highlights the necessity of the research. It elaborates on the objectives of the study that need to be fulfilled to successfully answer the research questions.

Chapter 2 (research approach) describes the selected research methodology that will be used as a template during the data collection phase. It covers different procedures and processes before stating the time horizon and explaining why it was the most appropriate and effective to be used for conducting the selected activity.

Chapter 3 (literature review) provides a concrete foundation for the study by focusing on the preexisting literature that has been evaluated and compiled to correspond with the aims and objectives of this research. This section will first identify the various IoT resources, digital servitization competencies, and subtler aspects of business performance before highlighting the major impacts of IoT on the remaining two variables.

Chapter 4 (results and analysis) highlights the results and data analysis techniques employed in the study. Empirical findings from chapter 3 will be examined and interpreted in this discussion section.

Chapter 5 (conclusion) marks the end of the study through the conclusion section. It highlights different recommendations made concerning the primary data obtained. It will focus on clarifying whether the study’s aims were met or otherwise provide insight into why they were not achieved. Future research areas will be suggested and any potential gaps in the literature that could impede the actual research will be addressed.

Research Approach

Introduction

This chapter will discuss the research paradigm, methods employed, timeframes, procedures, and processes, along with justifications for the strategies that the researcher selected.

Research Overview

Research Philosophy

The theoretical concepts connected to various philosophies are covered in the first layer of the research onion. Each choice made in this layer ultimately determines how the researcher will gather and analyse data to ensure the accuracy of the research’s overall conclusions. The pragmatic approach was used as the research philosophy in this study. This method focuses on identifying a problem in a broad context and leads to the further inquest to understand and learn more about the problem, which can then be solved. Additionally, the pragmatism approach was found to be beneficial to IoT-related research as it focuses on relevant processes. The answers offered typically included processes to be undertaken by SMEs to capitalize on a post-nascent trend (the Internet of Things). The pragmatic approach was very appropriate especially when considering the nature of the research questions because the solutions and recommendations had to be provided in the research’s conclusion.

Research Process

This study is divided into two phases namely, large-scale and pilot surveys. The main study will follow the design highlighted in the Research Onion by Saunders et al., (2009); a model created to define the various research methods and strategies. Figure 1, below shows each layer in this tool with the different methods and approaches that the researcher can choose from, which explicitly affect how the research will be conducted. The researcher chose the most appropriate modalities to be used in different stages of the study after considering all of the onion’s facets. More details about this instrument and the relevant techniques sought have been highlighted throughout this chapter.

Pilot Study Sample

Conducting a pilot study with a sample size of 10 before the main one would provide crucial information regarding the validity and accuracy of the instruments to be used. It is an effective approach for examining and evaluating the study techniques (Ancillai & Pascucci, 2021). In this context, the pilot study was conducted using Jisc Online Surveys, a U.K.-based Internet survey platform (https://www.onlinesurveys.ac.uk) via a 5-point Likert scale. The digitalized survey is appropriate because the targeted sample involves businesses, and coverage issues are unimportant given the high rates of internet connectivity and computer literacy in the U.K. The Jisc Online Surveys will contact SME managers based on their experience with IoT and the firm’s age. Table one below shows the different areas where the sample will be obtained.

Table 1: Geospatial Topographies for Sourcing Samples

Given the relevance of the current study to the existing literature, competent respondents were selected after a meticulous screening process. For instance, they had to have occupied senior positions such as managers, deputy directors, or CEOs and have awareness of the IoT culture within their company. Their duties must have involved supply chain coordination, information technology, manufacturing production, or digital practices related to the deployment of IoT in their firms. Although the Standard SME Classification code was not specified, individuals working exclusively in the service sector were excluded. To confirm that they are familiar with IoT, they were required to profile their experience with these digital systems.

The survey was expected to be completed by a total of 10 respondents. To ensure that the data was relevant, credible, and appropriate for statistical analysis, data pre-processing was first performed. Missing data, disengaged, and ineligible feedback was identified during this process. The second stage was to identify dishonest respondents who completed the survey in less than fifteen minutes or who merely provided one response (for instance, “I agree, I agree, I agree”) for each question (Frank et al., 2019). This was detected by basic observation and further verified through the computation of standard deviation.

A standard deviation threshold value of less than 0.5 was used to identify vague responses. To prevent unforeseen dimensions that were not conceptually defined, items should be refined before component analysis (Agrawal et al., 2021). The Corrected Item Total Correlation (CITC) was then computed for each item to serve this function (Kolagar et al., 2021). Any item with a CITC below 0.5 had to be removed. To calculate CITC and Cronbach’s alpha, IBM SPSS 25 model was used.

Research Process for Large Scale Study

The second layer of the onion revolves around choosing the best research strategy as either deductive or inductive. The deductive strategy entails beginning with a claim or a question, attempting to answer it through research and typically providing a conclusion that answers the claim or question with either a yes or no. The inductive method, on the other hand, focuses on gathering data to develop a theory.

This technique usually requires that the data is studied to highlight areas of emphasis and facilitate the development of new theories through analysis (Atif et al., 2021). This perspective is in line with that of Annarelli et al., (2021), who define inductive reasoning as a flexible organized technique that seeks to verify hypotheses based on actual data. Deductive reasoning, on the contrary, is portrayed as a highly structured method that tries to examine study concepts in light of the proposed hypotheses. Due to the need for assessment of individual study results on IoT and digital servitization, this research used an inductive technique. The general conclusion given at the end is based on the analysis of numerous academic literature and research participants’ results.

The study methodology and pragmatic approach enabled the author to analyse secondary data gathered for research conducted over the last five years to identify IoT factors that had been overlooked. This implies that the strategy provided an opportunity to easily identify potential research gaps. Additionally, the inductive method was used to develop new hypotheses by analysing the literature and its gaps, which would then provide answers to previously identified and emphasized research problems.

After the different prior studies had been examined and a survey conducted, the author provided solutions by sharing several recommendations that can be used by business owners to blend the Internet of Things components in their daily operations. Although the research topic was theoretically and practically validated using this technique, the need for future research on IoT-related concepts cannot be overlooked. The above-mentioned deductions could be easily identified because the entire research was driven by the inductive approach.

Research Methodology

A systematic review was utilized for the literature review section. This is a strategy whereby relevant research on a certain topic is thoroughly checked for, evaluated, and synthesized using a predetermined explicit method (Favoretto et al., 2022). The selection of a scope and a diligent search for pertinent topics are the initial steps in a systematic review. The exclusion criteria are applied during the search to determine whether or not the article qualifies to be included in the review. The literature is then examined to determine its quality before a decision is made on its inclusion.

Since the data to be obtained had to be objective, a systematic review was chosen as the method for data collection in the literature review. According to Flores-García et al., (2022), the conceptual analysis of research work in IoT and digital servitization would only be successful if the data collected was unbiased. Otherwise, the analysis could have been criticized as biased as it is based on the author’s predetermined point of view. The following were the exclusion criteria for this technique:

1. Does the journal discuss any digitalized trends present in business processes, product models, domains, and organizational structure transformation?
2. Does the article recognise any of the following common themes in IoT literature? (For example, digital business models, operating models, skills, and talent dimensions).

The relevant studies that met the aforementioned inclusion criteria were identified and then later evaluated to confirm their relevance. As there are diverse subtopics in the research’s existing literature, the systematic review in this study did not collect data relating to a single, narrowly focused research question, but rather on broad-based topics. The approach provided a thorough understanding of the technology lifecycle and trends in SMEs by taking an in-depth introspection at one or more events across different stages of firm development.

According to Flores-García et al., (2022), the following measures had to be taken to guarantee the accuracy of data from secondary sources:

1. The creation of a standardised literature database was introduced at the final stage of the data collection process.
2. All pertinent data and other pieces of evidence from the then-available databases were formally verified by the researcher.

The selection of criteria was pioneered by the fact that members of the research team could interfere with data by constructing a specific framework in an attempt to theoretically validate a misleading hypothesis. Both parameters required that the secondary data had been collected from highly reputable and credible sources (Kohtamäki et al., 2021a). These newly generated criteria were useful when giving a clear dimension of situations that triggered a technological transition in a firm’s lifecycle. The research team would then use the literature for the theoretical validation of this research’s hypothesis.

Research Hypotheses

Over the last decade, the level of human engagement in SMEs has been greatly reduced as a result of business owners’ propensity to integrate AI-driven solutions into their production cycles. As of 2021, the rate of IoT growth among SMEs across the U.K. was 54.9%, compared to 47.3% recorded in 2019 (Marcon et al., 2022). The automation of a company’s routine and operations is usually geared towards increasing production and customer satisfaction, which in turn boosts its financial performance.

On the contrary, the dearth of research on the impact of this decision on the subtle facets of business performance, however, has not been adequately addressed in pre-existing literature. In that regard, this study will focus on addressing critical but overlooked hypotheses (research questions) in existing digital servitization and IoT studies, such as:

1. What impacts does IoT have on supply chain efficiency among SMEs in the U.K.?
2. How does IoT have positive efficiency on digital servitization and supply chain among SMEs in the U.K.?

A study by Sisti, Estensoro, and Larrea, (2021) titled “The Interrelationship between Industry 4.0 and Servitization in Manufacturing SMEs” had contradictory findings thus emphasizing the need for additional research on this topic to clarify confusing facets. This issue will be addressed in the first hypothesis by assessing the possibility of linking digital devices to one another for the better supply chain management. The section below highlights how different literature reviews helped to shape this study’s hypotheses, its systematic review of different aspects of business performance, and ways in which this study can help readers improve their market.

Research Questions

The incorporation of modern technology and the Internet of Things will enable SMEs to maximally capitalize on emerging trends in the global market. This would eventually result in tremendous growth and sustainability improvement. Apart from addressing the impacts of adoption of IoT in SME operational cycles, this study encompasses theoretical and philosophical concerns regarding the complexity of some production processes that trigger servitization (Formisano et al., 2019). As highlighted earlier, many SMEs are already blending their production processes with the digital market trends.

However, the scarcity of literature on the aftermath of this move on finer aspects of business performance has been overlooked. In that regard, the three research questions to be addressed have been included below;

1. Are there ways in which SMEs can theoretically explore different servitization opportunities using available Internet of Things features apart from those already in use?
2. What is the significance of the Internet of Things in key practical business aspects such as supply chain performance and innovation among SMEs?
3. What are the overall outcomes of the use of IoT engineered digital servitization on SME growth and sustainability?

Mono/multi-methods

The approaches at this phase, identified as the mono method, mixed method, or multi-methods, are contained in the fourth stratum of the research onion diagram. The researcher is said to have chosen a mono-method if only one method is selected (either quantitative data or qualitative data) and mixed methods if they choose both quantitative and qualitative data throughout the study (Kohtamäki et al., 2021b). However, under the multi-method option, the researcher uses both quantitative and qualitative data, but the overall perspective of the study outlook is inclined towards one of them.

Since the mono-method analyses data from a narrow perspective, the framework of mixed methods was used for this study. The employment of both qualitative and quantitative data gathering and analysis techniques is referred to as using “mixed methods” in research. This has been chosen because qualitative data made it possible to explain the underlying benefits that the Internet of Things can provide through detailed and verifiable results.

Additionally, the method was applied to reviews and interpretations employed in this paper to provide a fundamental comprehension that inspires further research on IoT and servitization-related topics. Quantitative data made it possible to perform statistical and/or numerical analyses, which would be used to measure data and detect trends in digital servitization as well as understand the reason for the occurrence of certain technological transitions in a firm. In this study context, the qualitative analysis and evaluation phases of the mixed method helped in answering the study questions and fulfilling the goals that had been previously established. The researcher was obliged to adopt a multi-method approach because each stage of the study employed either one or two techniques.

Research Validity and Reliability

Research reliability is the degree to which the same results can be obtained if the same techniques were used to analyse data on different occasions. On the other hand, research validity refers to the production of study findings using rigorous research methodologies (Garzoni et al., 2020). According to these authors, the validity of a study is crucial for all forms of research. This study is valid because it adhered to the proper scientific research processes by making sure that the right time stamps and approaches were applied at different stages. To guarantee the validity, triangulation was conducted through an online survey during the pilot study. Similarly, none of the respondents was coerced to select a specific response for any of the questions. Thus, it is safe to say that these research results are credible since similar results will be obtained if different research processes are applied to this study.

Ethical Considerations

The following principles of ethics, as determined by Coventry University’s Research Ethics Committee, were followed during this study:

1. The research team was not at risk of any harm while conducting the research.
2. The confidentiality of the research participants was completely guaranteed.
3. Neither of the research objectives was exaggerated nor was the primary data collected manipulated in any way.
4. All participants in this study project, including individuals and organizations, had a right to receive the analysis feedback.
5. The acquisition of data from respondents received full consent.
6. All academic sources used, either implicitly or explicitly, were included in the bibliography section.

Time Horizons

The recommended temporal spans for the research are longitudinal and cross-sectional. Since the former can only to analyse trends and transitions over a significant timeframe, it would be unsuitable for this study considering the durational constraints that need to be observed. Therefore, the research team opted for the cross-sectional approach. This time horizon was the only viable option in this context because it focused on variations that occur within shorter spans. Nonetheless, with this selection, it was challenging to identify and evaluate current changes in technology during the study period due to the spontaneous nature of innovation.

Data Collection

Given that all the hypotheses highlighted in chapter three had to be numerically studied, qualitative analysis was greatly employed to explain specific patterns (and their implications) in results obtained from the sample studied. On the contrary, the quantitative representation and interpretation of findings were employed to interpret the study’s primary data. This involved processing data in its raw form using statistical frameworks such as the Structural Equation Models before a thorough analysis was conducted.

In this study, three phases of data collection were used to empirically evaluate the hypotheses presented in chapter three. Firstly, a systematic review was used to collect secondary data required for the research. This was necessary for drafting a thorough literature review that provided a clear conceptual definition of IoT, servitization, and business performance construct hence facilitating robust topic development. During this stage, necessary postulations were reviewed and verified by members of the research team. This method was ideal because the research required abstract data for the analysis to be objective. Conceivably, the research could have been pilloried as biased by asserting that it reflects the preconceptions of other authors and researchers.

Secondly, a 30-minute online survey was conducted via Jisc whereby Likert scale questionnaires were sent to a placebo group consisting of 40 firms. The questions were drafted based on the two hypotheses and respondents were required to answer them by ticking within the appropriate slot. The results of the placebo group would then be used to evaluate the instruments’ construct validity and reliability as well as to improve the clarity of the questions. During this phase, relevant adjustments were made to maintain the study’s generalizability. Lastly, a large-scale study was conducted and it involved the use of open-ended mail questionnaires. Although the respondents were expected to answer all questions accordingly, those who wished to withdraw from the study had a chance to do so. Table 2 below shows the sample data from a large-scale study.

Table 2: Sample Data from Large Scale Study

The data collected was then fed into SPSS software for analysis and interpretation.

Therefore, the study made use of both the qualitative and quantitative classes of data. This is because the means of data sources included journals and books which usually contain statistical tables and charts that show the different wave technologies that have been presently developed and tested. Table 3 below summarises the different research approaches used for data collection and validation during this study.

Table 3: Data Collection and Validation Approaches

Triangulation

Triangulation refers to the process of combining various data collection techniques and standpoints to strengthen the authenticity of the study findings. This is achieved by integrating at least two research approaches or procedures on a single phenomenon. Triangulation can be utilized to guarantee validity by avoiding the use of a single approach while enhancing the reliability and credibility of study findings (Kohtamäki et al., 2021a). This research used the Jisc Online Surveys to conduct a pilot survey that would then supplement the open-ended mail questionnaire technique in the large-scale study to either oppose or support the topic. A total of 10 SMEs from three regions were enrolled in a week survey. Study results from this process helped to minimise sampling, measurement and procedural biasness in the large-scale study.

Project Realisation

This research adopted the five key steps in realistic planning to steer it towards a successful conclusion. Setting attainable goals, prioritizing each task in research, scheduling meetings with the research supervisor, and allocating time for unrelated research tasks were all part of this process. Potential risks were mitigated through avoidance by strictly operating within the study’s timeframe. A detailed methodology with clearly defined goals for each week was established to minimise the possibility of risks.

Conclusion

This chapter has demonstrated how the research’s objectives would be achieved by summarizing its approach. The research employed both quantitative and qualitative data among other approaches, with each stage utilizing a specific set of techniques to achieve each goal most efficiently. The summary of all approaches selected for this research methodology is displayed in table 4 below.

Table 4: Summary of Selected Approaches

Systematic Review of Preexisting Literature

Introduction

The previous chapter introduced different methods that will be applied in the actual study and highlighted their appropriateness in this context. This chapter examines pre-existing literature on IoT, servitization, business performance, and digitalization and provides the timeline and development of IoT elements. The interrelationships between IoT and other aspects of business performance aspects such as product diversification and supply chain have been discussed. Throughout this section, previous perspectives and findings by other authors have been compared with the deductions and inferences in this study. Similarly, how the literature reviews (from these authors) helped to shape the study’s research questions have been elaborated

IoT and Servitization Timeline, Commercial Aspects, Value in Business Management, and Downsides

Internet of Things (IoT), refers to a group of digital resources that can be interlinked and programmed to perform simple and complex tasks with minimal human intervention. The origin and history of digital devices date back to 1982 (Paiola, 2018). That year, students at Carnegie University connected a vending machine to a computer using the school network, enabling them to check the temperature of drinks in these machines.

A decade later, John Romkey developed a toaster that could be completely controlled by the Internet. This invention was later transformed into the world’s first webcam prototype in 1993 (Pham & Vu, 2022). In 1999, Kevin Ashton postulated the phrase “the Internet of Things” while presenting a project on RFID at Procter and Gamble (Paiola, 2018). Although Ashton’s concept of an RFID-based device network is different from the current IoT Internet Protocol, his innovation remained crucial to the history of the IoT and the advancement of technology as a whole.

The Nabaztag, a forerunner of smart home technologies like Google Homes and Alexa, was created in 2005. This device was coupled with speech capabilities that could inform its owner about the weather conditions, the price movement in the stock market, and Website feeds (Pham & Vu, 2022). Later in 2014 and 2015, IoT-sensor-based devices and smart cities began to emerge respectively (Paiola, 2018). This was followed by IoT infiltration into the healthcare sector in 2018. By 2020, wearable medical equipment improved in quality, giving healthcare workers efficient access to patients’ data during the COVID-19 pandemic (Annarelli et al., 2021). Since then, there has been rapid innovation of new and more sophisticated technological gadgets, totalling approximately 15 billion as of 2021.

IoT Use in the Last Five Years

IoT began to infiltrate the healthcare and health insurance sectors in early 2018. The Internet of Medical Things was used to describe this trend whereby healthcare professionals could access patients’ data and monitor their recovery using digital devices (Schiavone et al., 2022). By 2019, IOMT had introduced digital detectors in defibrillators, thermoregulators, blood glucose, and heart rate monitoring systems. Later in 2020, IoT was employed to accelerate the response to the COVID-19 pandemic (Ricci, Battaglia & Neirotti, 2021). Infrared software and sensor camera were used to detect heat radiations from patients while digital thermometers were used to measure body temperatures in public places without the need for physical contact.

In the following year, the rate of spread of COVID-19 reduced thanks to smart building features that facilitated the conduction of rigorous clinical trials whereby different plant-based vaccines were tested for efficacy. Similarly, IoT proved useful in connecting heating, ventilation, and air conditioning systems in COVID-19 isolation zones during this time (Schiavone et al., 2022). In 2021, the Digital Around the World Program (DAWP) organised an IoT forum, giving its members a chance to collaborate with other stakeholders across the globe. The decision reached by the forum allowed different industries and their subsidiaries to benefit from IoT.

Commercial Aspects of IoT

Commercial aspects of servitization (digital services) are usually covered under commercial IoT. The latter phrase alludes to all digital equipment and systems used in different models of industries and businesses. Since IoT is being used more frequently in sectors like healthcare, office buildings, and logistics, a wide range of devices are typically integrated to perform specific functions (Marcon et al., 2022). Businesses have been able to explore new transaction opportunities thanks to modern technologies like 5G and artificial intelligence. Heavy machinery in large production plants can be connected to a virtual control system and the data from connected infrastructure and smart meters be remotely monitored by utility companies. On the other hand, IoT has been helpful in the medical field through devices that are capable of informing doctors about patients’ prognoses. With IoT analysis, farmers can maximize their yield, making it a remarkable asset for nearly all businesses.

Value of IoT in Business Management

The Internet of Things can be used to assess employee performance and engagement thus optimizing the entire business management process. It has become simpler to gain insights into aspects like customer preferences and new product performance thanks to the availability of IoT-driven big data that facilitates decentralized collection and exchange of data. Regarding logistics, when specific conditions are met, IoT systems can facilitate the conduction of supply chain transactions in some industries on autopilot. With the help of IoT, businesses can manage their workforces, provide better customer service (help desk automation), and enhance their offerings in the market. Concomitantly, IoT can strengthen the network and links between different individuals and firms involved throughout the product production and sale processes, thus improving logistics.

Decent Instrumentation Technologies

Given their widespread use and popularity, smartphones, mobile computers, camera phones, and other portable technologies have made the idea of IoT marketing easier to implement. Hand-held digital devices have assisted businesses in the discovery of mid-funnel yet pertinent clients within close vicinities. This is possible by merging such gadgets with geofencing (a technique which uses geographical data from a smartphone’s in-built sensors to direct potential customers to adjoin enterprises). Whenever a prospect is traced, IoT-smart devices at the firm alert the sales team to send relevant messages (a superior product proposition) to distract the customer from buying from the competitor. Burger King, for instance, successfully implemented this IoT model in 2021 through the “Whopper for a Penny” promotion. In this technique, customers who were within a 450 meters radius of Burger King’s competitors would get a notification on their phones (Annarelli et al., 2021). The message’s aim was to redirect recipients to any nearby Burger King food joint.

The Downside of IoT

Whereas IoT digital devices have been associated with a wide spectrum of benefits, shortcomings that can accompany the use of these devices cannot be overlooked. These limitations are discussed below.

Technical Complexity

Although the Internet of Things (IoT) devices can perform basic tasks, such as counting swipes at security checkpoints, they employ a lot of intricate technology. With this in mind, if the devices are generating crucial data for another workflow or system, they may compromise all of their associated processes. Whereas counting swipes can be deemed a simple task, it can be detrimental if the device miscounts swipes and thus feeding false information to the detection servers in the subsequent systems within the digital conveyer belt.

Higher Installation Costs

IoT device deployment often requires a significant amount of time and financial investment. This is because there are different devices that must be procured and personnel who must be hired to install and link them to the manufacturer’s network and system. Although businesses can quickly recoup their investment, the high initial and maintenance costs required cannot be overlooked. However, businesses can override these potential barriers by organizing the deployment budget and strategy before venturing into this niche.

How IoT and Servitization Link and their Correlation with Supply Chain

IoT and servitization in logistics the business in its entirety are linked through four main elements namely; routine automation, information flow, budget cut, and M2M communication pathways. These four constructs discussed below are the digital drivers which propel business models to automate their operations and services. Similarly, the drivers are useful in different logistics stages namely, operational, demand, product, supply, and sales planning as highlighted throughout the following sections.

Routine Automation

One of the major reasons for increased cases of IoT incorporation in business and supply chain is its capacity to facilitate automation. With the help of IoT, recurrent business operations like inventory control, accounting, and the management of staff work schedules can be easily conducted (Pham, 2019). The review in this context confirms this author’s perspective since it was established that entrepreneurs and managers have been able to identify specific tasks that are crucial for the development of their business through automation. It was further found that duo can separate recurring tasks from those that are only operationally required but not directly related to their strategic goals. Finding techniques to automate some repetitive operations results in significant time and labour savings (Paiola, 2018). Automation does, however, come with some hazards that need to be reinforced by cybersecurity measures.

On the other hand, firms can benefit from IoT by automating their lengthy operational planning procedures with smart protocols to update supply chain projections in real time. Collaboration across the organization is made possible by implementing automated real-time operational planning systems. As a result, when an unexpected event occurs, managers in the logistics department deploy their resources rapidly to buffer uncertainties associated with such unforeseen circumstances.

Circular Flow of Information

SME owners in every industry can gain access to thorough information regarding the operation of their companies as well as learn to analyze qualitative parameters related to the behavior of each client, employee, and firm’s success. Digitalized analytical systems and visualization tools can be used to effectively process customer-related data. IoT gadgets have proven to supplement traditional communication methods like voice calls, emails, and even teleconferencing by elevating the need for physicality to a new level of connection.

Understanding what customers want and when they want is a recurring problem for many packaged goods manufacturers especially during the product and sales planning stages of supply chain. To perceive consumer demand signals correctly, an IoT-focused solution such as Anaplan reduces information asymmetry throughout the supply chain by going beyond the shallow network between wholesalers and retailers (Ghosh et al., 2022). Additionally, businesses gain a better financial performance and improved lead times when shifting consumer sentiments are quickly detected in a seamless flow of information patterns.

Budget Cuts

The Internet of Things has proven to be beneficial to all types of enterprises and companies in the SME sector by reducing their general expenditures and enhancing productivity. Although the costs involved in implementing sensors and updating devices and networks to host the analytics platforms are high, SMEs will benefit almost immediately from staff cost savings. This is because the technology incorporated effectively solves issues to which they previously had to devote significant time and manual effort. According to (Dutta et al., 2020), the majority of SMEs dealing in logistics and freight services can virtually automate nearly all their procedures if the IoT flourishes into a generalized standard by 2030.

Business’ supply planning models sometimes become wider and more costly to monitor since supply chain planning often incorporates different clients, price plans, and channels. This is usually evident where spreadsheets are the main planning instruments (Formisano et al., 2019). Implementing IoT solutions that leverage real-time data lowers these expenses and lessens the possibility of stock-outs or overstocking for the company.

M2M Communication Pathways

It is easier to control operations remotely if IoT is utilized to integrate business hardware into manageable components of a single network. This is pioneered by the feasibility to oversee an entire production line or warehouse using a mere tablet and a broadband connection (Paiola et al., 2021). This review concurs with the viewpoint of these authors since different industrial machine systems that use local displays to illustrate the operational status of the production chain can receive input from a variety of auxiliary sensors. Sensors, when linked to the networks in the plant, can transfer real-time data that is then analyzed and utilized for preventative maintenance programs. Additionally, it can be used to modify production settings and synchronize other countless pieces of equipment within the firm (Ghosh et al., 2022). The IoT’s M2M communication pathways, which are its cornerstone, are assisting in lowering production chain expenditures incurred by SMEs hence the reason for widespread IoT inception.

To a greater extent, supply chain management currently relies on historical forecasts. However, machine learning and artificial intelligence are poised to revolutionize this trend permanently. Logistics processes such as demand sensing, structuring, and synchronization are being transformed by AI- and ML-based predictive frameworks engineered by M2M communication pathways. The duo has been proven to push new product models beyond the constraints of product promotion alongside eliminating supply chain interruptions. Concomitantly, new product launches and dynamic pricing models based on anticipatory market intelligence are being propelled by the use of AI and ML.

Critical Issues Review: Servitization and Digitalization

Servitization is one of the most competitive trends in the modern business world which requires potential customers to pay for a service instead of purchasing the equipment that offers it. In the SME industry, servitization takes different forms, one of them being digitalization. Digitalization refers to the process of initiating, enhancing and/or modifying business operations and/or processes, through the use of digital resources (Formisano et al., 2019). As already emphasized by Tudor et al., (2021), in this research, we regard digital servitization as a method of altering core business activities through the Internet of things technologies.

Although digital transmutability in businesses can take different forms and approaches, a shift from one mode of purchase for a product to the other does not imply servitization. For instance, the shift from Office 365 to Microsoft 365 by Microsoft in 2020 cannot be categorized as servitization (Kolagar, Parida & Sjödin, 2022). Whereas the new service added capabilities to the application’s toolkit, a monthly fee of $7 for an individual plan or $10 for a household of up to six people had to be paid by all customers (Kohtamäki et al., 2022). Microsoft aimed at converting the vast majority of its Office users to annual subscribers, which in the long term generated more revenue.

Customers who had initially purchased these services through the company’s CSP plan were bound to consider the new pricing model, which was comparatively more expensive than the previous one. There were several petitions filed against this transition as it was deemed to be an exploitative move by the company to maximize profits, implying that the latter did not consider consumer satisfaction as in the case with servitization (Pham, 2019). According to Markfort et al., (2021), the changes were tailored toward lowering the micropayments (month-to-month subscriber) loss for the company rather than transforming the business from product-centricity to product service orientation.

Digital Servitization Constructs

The process of digital servitization, pioneered by IoT, can be categorized into three main elements namely, monitoring, automating, and managerial constructs.

Monitoring Construct

The capacity of an enterprise to identify and gather information on its processes, third-party logistics, product features, and services, as well as its environment constitutes the monitoring competency. To sustain competitive advantage needs organizations to be acquainted with the shifting of market sentiments, customers, and competitors who are likely to steer the said firm in this direction (Kaňovská & Tomášková, 2018). However, from a firm’s internal perspective, its ability to gather and evaluate these signals as inputs for decision-making processes is crucial.

The Internet of Things equips SMEs with end-user devices and sensor systems (connected through the IoT Cloud) necessary for monitoring deviations and anomalies occurring both within the organization and at the clients’ level. This data is then processed into useful knowledge and insight that aid SMEs in decision-making (Grubic, 2018). Businesses with a high level of this competence would be able to recognize and seize opportunities and risks in their respective operational contexts.

Automation Construct

By utilizing IoT technologies, a company can explicate and standardize the operations of its product services and processes with little to no human involvement. According to the dynamic capability paradigm, automating construct is a subset of a firm’s reconfiguration ability (De La Calle et al., 2020). This is because, to automate operations, businesses must realign and coordinate their relevant processes, streamline their operations, and enable cooperation with a significant level of subsidiarity.

Managerial Construct

Managerial construct refers to a firm’s ability to use IoT technology to control its operations, services, and distribution channels. This choice would motivate businesses to invest their efforts and capital necessary to innovate and provide customers with a new value (Mesquita, Simões & Teles, 2022). Businesses must evaluate any potential risks linked with this competence as a necessary precondition for their success. New client relationships, resource reorganization, and a redefined business model are all necessary to support this initiative.

Impacts of IoT on Business Performance Aspects

Figure 2 below shows the proposed model that links IoT to Digital Servitization and Business Performance.

IoT Digital Incentives and Supply Chain Management

IoT provides a business environment that can connect SMEs’ systems directly to their owners and supply chains. It makes it possible for smart devices to link to one another, allowing for stable and reliable real-time communication between them as well as comprehensive visibility, traceability, adaptability, scalability, and flexibility of the entire system. Therefore, incorporating IoT systems by SMEs would result in a variety of benefits, such as accelerated logistic processes, resource optimization, reduced risks, and reduced overhead expenses (Ricci, Battaglia & Neirotti, 2021). Similarly, the supply logistics department can depend on the Internet of Things (IoT) to facilitate real-time tracing and tracking of inventory.

The use of IoT is recommended as a solution to issues like low levels of engagement among joint warehousing partners. The deployment of a bottom-up approach in warehouse management would be made possible by its digital infrastructure and technologies, which include Radio Frequency Identification, AI-controlled surveillance infrastructures, and sensor systems (Martín-Peña, Sánchez-López & Díaz-Garrido, 2019). The aforementioned tools would not only reduce the need for regular manual inspections but increase warehouse traceability as well (Schiavone et al., 2022). Thus, subtler aspects of warehouse management’s responsiveness in a dynamic business environment are easily improved or favourably modified.

Although the impacts of IoT on the supply chain have already been established in pre-existing literature, there are only a few research studies that adopted a cross-sectional time horizon (Motohashi & Rammer, 2020). As a result, hypothesis two was formulated since the researcher deemed longitudinal studies’ capability and ability to analyse change and growth over a long period inappropriate. If the correlation between these two variables is found to be positive, then readers can use this review to guide future studies based on existing durational constraints.

Efficiency of IoT Digital Incentives: Servitization (Digital Services) and Supply Chain

Different processes are involved in the movement of raw materials from suppliers to producers and the delivery of finished products to the customer. The integration of these daily operational activities with contemporary technology and the Internet of Things will enable SMEs to accrue remarkable benefits while at the same time staying updated with new trends in supply chain department. As a result, their desire for profit maximization, coordinated logistics, and improved sustainability could be easily achieved. This study examines conceptual and philosophical issues regarding the intricacy of specific production and logistics processes that would be facilitated through servitization in addition to addressing the impacts of IoT adoption in SME operational cycles (Formisano et al., 2019). As cited earlier in the introduction, approximately 57% of small businesses, are unable to achieve digital transmutability goals due to inadequate information that supports the adoption of rigorous technological solutions.

Technology on inventory control and business logistics management is evolving extremely fast while research on its resultant business opportunities lags, thus necessitating the need for hypothesis two. If the relationship between IoT and new business opportunities is found to be statistically significant, then the reader can use this review to improve their understanding of new trends in the market. Readers will be better positioned to prioritize opportunities as they arise while concurrently mitigating potential risks that could be associated with them. By blending the latest servitization trends into their methods of production, entrepreneurs will be able to capitalize fully on emerging opportunities.

IoT and Marketing (Digital Product Campaigns)

The first stage in digital marketing usually involves the installation of sensors into the company’s digital accessories for IoT connectivity. The existing customers are then allowed to share their data on preferences, which is later transmitted back to the firm’s network for insightful analysis. This is because such customers are more receptive to new value propositions hence reliable for cross-selling techniques. Due to the expenses of running different marketing systems, this is perhaps one of the more expensive IoT-application instances, however, its benefits are undeniably far-reaching. For instance, in 2021, Diageo, a beverage corporation, designed personalized whisky bottles to encourage user-generated product video clips (Marcon et al., 2022). This campaign eventually increased product’s popularity and, consequently, sales by 66%.

IoT and Big Data Mining

Conventionally, Big Data is defined as the practice of assembling a sizable data set from digital devices, such as actuators and sensors in a smart environment. Such information is then used to assist in the monitoring different business processes, macro environmental factors, and system performance. Most firms find it difficult to rapidly and effectively collect pertinent information for monitoring such aspects due to the rapid dynamism in business sentiments. As a result, Automatic Text Summarization, a big data mining tool, has gained popularity as a solution to this issue due to its ability to effectively compact data from enormous text corpora. SMEs can employ a variety of cutting-edge modalities for data mining, including genetic algorithms, aggregation networks, and swarm optimization among other hybridized methodologies (Motohashi & Rammer, 2020). Similarly, modern IoT software allows for the customization of the most recent and pertinent algorithms, an opportunity that firms can leverage in data mining.

IoT and Plant Maintenance

With the help of new technology, maintenance solutions are becoming more effective, resulting in reduced entropy and enhanced equipment durability and uptime. The use of reactive maintenance is not only costly but further reduces production efficiency by forcing businesses to wait until machines malfunctions before fixing them. Concomitantly, the lifespan of the equipment is typically shortened by this technique, which escalates machinery’s life-cycle expenses (Marcon et al., 2022). Therefore, IoT-based maintenance, which constantly evaluates the status of assets via real-time tracking, can significantly improve the viability of equipment and reduce downtime. With this method, businesses can spot trends in the variables that, when considered collectively, have an impact on the functionality of equipment and formulate timely preventative measures.

Literature Gaps

SMEs have been actively pursuing possibilities for profitability and expansion through the incorporation of IoT-driven operation and digital servitization competencies. However, studies on how IoT product systems assist SMEs in improving their servitization efficiency and subsequently, the performance of firms and supply chains are yet to be established and tested through extensive survey-based empirical studies. This corpus of research yields considerable discrepancies in findings regarding the impact of the use of these systems on digital servitization, as there are only a few tested roadmaps for using IoT product systems (Pham, 2019). The two aspects constitute one of the literature gaps that this study seeks to address.

Concurrently, for a long time, enterprises and organizations in the SME sector, both large and small, have prioritized digital transformation owing to the need to survive in a highly competitive global market. The recent decades have experienced high interest regarding the need for cloud-based digitalization, with new product service systems emerging every day. According to 57% of small business owners, however, the major obstacle to achieving digital transmutability goals is the lack of defined frameworks that support the adoption of rigorous technological solutions (Motohashi & Rammer, 2020). This slows down the deployment of IoT resources for firms that may be primarily focused on the uncertainties associated with this trend. Therefore, this study will test the impacts of dynamism in market sentiments on new product performance beyond the supply chain before providing recommendations to mitigate them in attempts to bridge this gap.

Concomitantly, it can be overwhelming for late adopters to make the right decision on which path would be most convenient when chosen. Early adopters, on the other hand, might remain stuck in obsolete technologies due to their uncertainties about newly invented models. Whereas the IoT incentives and key drivers can be easily accessed, SMEs are incapable of fully leveraging IoT’s potential due to the fore-cited discrepancies in adaptability and use of new production modalities (Marcon et al., 2022). This study seeks to contribute to pre-existing literature and mitigate the above gap by exploring ways in which IoT, servitization, and digitalization are interconnected and how the former can improve SMEs’ operation bottom line. It will further explore how SME owners can improve business processes through technology.

Additionally, although the impacts of IoT on the supply chain have already been established in pre-existing literature, there are only a few research studies that adopted a cross-sectional time horizon (Motohashi & Rammer, 2020). As a result, hypothesis two was formulated since the researcher deemed longitudinal studies’ capability and ability to analyse change and growth over a long period inappropriate.

Lastly, there is a contradiction of automated supply chain efficiency results in the study documented by (Sisti, Estensoro & Larrea, 2021) under the title “The Interrelationship between Industry 4.0 and Servitization in Manufacturing SMEs. This further necessitates the need for more studies in this niche to demystify these confusing aspects. Hence this research builds and tests a paradigm for evaluating the effect of servitization and digitalization on logistics overall performance to fill existing literature gaps and resolve such contradictory results.

Conclusion

The purpose of this systematic review is to qualitatively describe the various approaches to IoT, business performance, and servitization concepts while concurrently exploring the first three study objectives and two hypotheses. Different aspects of digital servitization and the Internet of Things have been elaborated and this will serve as a foundation upon which the remaining chapters will be built.

Results and Analysis

Introduction

The previous chapter explained different constructs of digital servitization and IoT incentives. Their relationship with business performance was established from a systematic review of pre-existing literature. This chapter supplements the literature on servitization practices and capacities by confirming the usefulness of the Internet of Things in the development of digital servitization, which in turn improves a firm’s performance. The findings from this analysis support the evaluation of the literature that was outlined in chapter 3 by demonstrating the significance of the statistical correlations between IoT, digital servitization, and SMEs performance. Similarly, this section enhanced the field of research through the unique operationalization of IoT drivers and digital servitization constructs, as advised by Pham, (2019).

Results of the Pilot Study

Data from the Jisc-based pilot survey was examined for validity and consistency using the SPSS Cronbach alpha methods. Based on the following cut-off values, the resulting structural model offered an excellent match to the data: SRMR=0.06, CFI=0.91, CMIN=1.67, pClose > 0.007, and RMSEA=0.62 (Somohano-Rodríguez, Madrid-Guijarro & López-Fernández, 2022). Findings regarding the relationship between digitization, servitization, and business performance support all two hypotheses since the structured model’s goodness-of-fit metrics were all satisfactory.

To verify that the structural model has a standardised fit, the overall model fitness was first tested. The required cut-off values were attained by each of the fit indicators. The precondition that the RMSEA should not exceed 0.05 was rejected due to the lack of a close fit since pClose was less than 0.05 (Paiola et al., 2022b). Although the research model was acceptable, major external factors affecting SME operations such as government policies had to be accounted for. The results of the hypotheses were approved when the structural model was found to have a reasonable fit. Table 5 below summarises the results of the SPSS 25 analysis along with the suggested relationships, standardised regression coefficients, and their p-values. Since there were no convergent and discriminatory concerns, neither of the IoT digital pathways was eliminated.

Table 5: SPSS 25 Analysis Results

From these results, the CITC scores of all entries were all higher than 0.5, hence none of them was eliminated. Similarly, the Cronbach’s Alpha values obtained were higher than 0.60, indicating validity.

Results of Hypothesis Tests (Large-scale Study)

Businesses capable of linking both their internal operations and the macro environment can easily maintain a competitive advantage. This duality capability includes factors affecting market monitoring and customer association (Paiola et al., 2022a). Currently, many SMEs are using modern technologies to detect emerging consumer, market, and competition trends and enhance their outside-in capabilities (Kaňovská & Tomášková, 2018). IoT product systems can significantly enhance a firm’s duality capabilities by giving them access to real-time data about clients’ behaviour and product performance to help them adapt to changing market conditions (Tronvoll, Kowalkowski & Sörhammar, 2021). Customers’ tastes and preferences are made available to businesses through IoT product systems, making this information a valuable external resource for the creation of new products.

Additionally, the quality and efficiency of firms’ products as offered by IoT product systems would assist manufacturers in effectively resolving issues and developing plans to enhance their subsequent product generations. This benefit reduces the time needed for product development by taking into consideration misconceptions if this information is obtained from the customer directly through interactions (Paschou et al., 2018). Customer insight would directly influence accelerated innovation and the variety of products and services, particularly new product design (Naik et al., 2020). Therefore, it is suggested in this revised structural model, that access to customer data will have a favourable effect on the efficiency and servitization of new product development.

Discussion of Hypotheses Testing Results

Table 6: Coefficients for Study Hypotheses

• All values truncated to 2 d.p
• CR= composite Reliability.
• D=Deviation
• MV = Mean Variance
• ^Log transformed to reduce skewness.
• Coefficient alpha presented diagonal-wise.
• ^^p < 0.04 (double-tailed).
• ^^^p < 0.05 (double-tailed)

IoT is Positively Related to Supply Chain Efficiency

IoT and digital supply chain management are linked, hence it is believed that the adoption of IoT and servitization would improve the performance of SMEs’ supply chain. Although this connection is only partially statistically significant (p=0.1), the results from AMOS 25 analysis indicate that IoT is negatively associated to supply chain performance (r= -0.275). Therefore, the idea of new product innovation should be introduced to understand the nature of this correlation (Ricci, Battaglia & Neirotti, 2021). It is possible to take the results to mean that the advent of IoT might enhance product diversification, which would then result in an improvement in supply chain configuration. The challenges faced by SMEs when retrieving and processing customer information can be overcome when complexity and the associated amount of information are buffered. This problem can be explained using the idea of constrained rationality.

The capacity of SMEs to process information has some boundaries that can be exceeded if and only if customer data is adequately considered. Once this happens, businesses will be able to accurately adapt to a new trend, and their reaction to additional information regarding the product is markedly more logical (Ricci, Battaglia & Neirotti, 2021). One requirement for optimum IoT performance is that the firm and its supplier base must have a thorough understanding of how modules interact best with one another. However, this condition is typically violated when businesses and their suppliers, trying to modularize goods cannot agree on clear functional connectivity and interface homogenization (Kowalkowski, Bigdeli & Baines, 2022). Due to these bottlenecks, supply chain stakeholders experience additional costs and delays (Münch et al., 2022). Therefore, the efficiency of IoT technology in the supply chain is hampered by the lack of defined protocols.

Additionally, IoT product systems are usually complicated since they include hardware and software that seamlessly interact with one another on autopilot. This increases supply chain costs since they demand a particular level of skills and training to deliver services or choose suppliers (Ng & Wakenshaw, 2017). It is difficult to predict how the IoT will develop and whether it will affect supply chain efficiency. The results of this study, however, demonstrate that IoT is positively correlated (r =1.11; p>0.001) with supply chain performance. In this model, supply chain cost and consumer relations were used to gauge supply chain performance. This finding suggests that improving customer relations and supply chain performance is possible through the provision of information regarding new services offered to customers (Kohtamäki et al., 2022). IoT-driven supply chain management was confirmed to improve a business’s ability to efficiently monitor, manage, and expedite delivery in the logistics department as previously postulated by Kohtamäki et al., (2021a).

It was further established that IoT-enabled traceability enhanced overall company performance (r=0.466) by having a positive effect on a firm’s digitalization architecture (that is, monitoring, managerial, and automation aspects). This correlation was statistically significant at 0.001 (p=0.001). This result is consistent (in different ways) with earlier qualitative studies penned by Martín-Peña, Sánchez-López & Díaz-Garrido, (2019), Motohashi & Rammer, (2020), Ricci, Battaglia & Neirotti, (2021), and Schiavone et al., (2022) as highlighted in the literature review. Their selected case studies illustrated how SMEs can recognize and track their inventory, detect anomalies, and improve production by using real-time supply chain data generated by defined IoT systems.

IoT infrastructures, such as trace systems, and global positioning networks, are crucial to a firm’s success in the context of product delivery. The implementation of IoT technology by SMEs has proven to enhance their flexibility capacity and asset safety. In turn, having this capability aids businesses in increasing customer satisfaction. When this equipment is working at its full efficiency, SMEs can shift their attention to other crucial activities such as new product development and expansion of economies of scale. With this insight, businesses can digitize their supply chain functions with confidence.

IoT Has a Positive Influence on Rapid Innovation and Product Service Diversification

Digitalization can influence the results of innovation as an adjunct resource. With that in mind, this study investigated how digitalization might affect the effectiveness of a business in designing new products. The outcome of the data analysis demonstrates a positive and substantial relationship between digitalization capability and the performance of new products (r = 0.864, p>0.001). The conclusion of a related study by Rebelo, Pereira & Queiroz, (2021) showed that automation (one of the digitalization constructs), significantly contributes to the success of new products. The likelihood of obtaining a positive correlation on this hypothesis was mentioned in several qualitative pieces of research penned by Ng & Wakenshaw, (2017), Tronvoll, Kowalkowski, & Sörhammar, (2021) and Garzoni et al., (2020) highlighted in the literature review. Monitoring how consumers use a firm’s products and how they meet customers’ preferences would give the company significant information related to ways of enhancing the design and dependability of its product services.

Businesses can focus on finding the alternative configurations that work best for each distinct client through the process of developing, converting, and exchanging ideas with customers and enhancing flexibility. A business that uses a high level of automation is economical and more innovative. Process automation dramatically reduces resource wastes, lowers risks, and increases feedback delivery, efficiency and response time hence more attention can be diverted to product diversification. To adapt to opportunities or unfavourable factors from the external business environment such as government legislation (taxation), SME owners need to make adjustments to their processes or resources. Businesses with an advanced IoT competence would be able to quickly alter their product presentation techniques through renaming, re-pricing, brand extension and repackaging to mitigate such risks (Marjanovic, Rakic & Lalic, 2019). As a result, they can easily take advantage of new transaction possibilities, thus enhancing their chances of success. Managerial competency, backed with IoT-enabled innovation was found to assist businesses to employ resources efficiently and effectively, optimising output, reducing expenses, and enhancing their general adaptability.

IoT Exerts a Positive Influence on the Number of Business Opportunities Available to SMEs

The IoT system’s components can be transformed and reconfigured to satisfy various business needs. This enables the IoT ecosystem to scale and be highly customizable to offer new transaction opportunities (Marcon et al., 2021). These authors reported that the flexibility of IoT can have a substantial impact on the available business opportunities in their review of the literature and research on the “Capabilities Supporting Digital Servitization.” This study suggests that IoT-enabled device flexibility would have a favourable impact on a firm’s automation framework and increase its chances of creating and exploiting more opportunities in a highly competitive market.

The above correlation is statistically significant, according to the data analysis outcome for this study (p = 0.001). According to Mesquita, Simes and Teles, (2022), IoT-aided flexibility would assist with production scheduling, monitoring, and automation. This would be applicable in the context of rising attention to customizable business systems in response to the significant variations in client needs. This study’s result demonstrates that IoT product system configurability helps SMEs become more adept at digitalization through monitoring, managerial, and automation constructs, thus creating new channels for transactions. SMEs need to have the capacity to rearrange their IoT structure to respond to economic trends and manage critical changes in operations (Garzoni et al., 2020).

Based on the definition of servitization provided in chapter one, the term ‘business opportunities can be interchangeably replaced by servitization. Over the past five years, there has been growing scholarly attention to how digitalization can assist servitization. Many studies have recognized digital technologies as key drivers of servitization and increased transaction opportunities. However, there is limited knowledge on how the Internet of Things supports the two aspects (Opazo-Basáez, Vendrell-Herrero & Bustinza, 2021). This study, alongside that penned by Formisano et al., (2019)-highlighted in the literature review-suggests that monitoring, managerial, and automation constructs used in digital servitization (with IoT support) would enhance business performance.

This hypothesis is supported by the results of the AMOS multivariate analysis. It was discovered that digital servitization has a positive impact on servitization (r = 0.928), and this link is statistically significant (p>0.001). Virtual technology would assist SMEs in reducing risks associated with new opportunities through an improved understanding of how business trends emerge thus boosting the efficiency of operations. This result shows that IoT helps SME owners recognize the potential benefits of trending opportunities in conjunction with confirming that IoT aids in identifying the risks associated with servitization (Motohashi & Rammer, 2020). Therefore, they will be better positioned to approach their clients with new products because of this knowledge.

IoT is Positively Related to SMEs’ Financial Performance

This research suggests that IoT is positively linked to firm performance. This relationship is typically constrained by the timeframe of the product development process and the frequency at which new products are being released into the market (Paiola & Gebauer, 2020). New product development has been proven to have been significantly beneficial to a firm financial success in terms of gross profit and aggregate sales (r= 0.571, p=0.001). This outcome is in line with the empirical inferences in the literature penned by Saniuk & Grabowska, (2021) under the influence of new product development and IoT-enabled budget cuts (discussed in the literature review) on a business’s financial performance. However, there is limited empirical research on whether adopting rigorous product development improves firms’ performance, thus creating a potential gap for future researchers.

This study’s result further identified that product development would help the company earn more revenue in the long term by buffering supply shortfalls and operational costs. Similar shortcomings are induced by potential technological risks, accelerated marketing efforts, and the possibility of losing profitable radical innovation (Pham & Vu, 2022). Fundamentally, this finding may help to explain why many SMEs experience stable cash flows after the successful development of new products and reduction of operational costs through the automation construct.

For most businesses, the data collection process during the pre-servitization phases is usually characterized by high costs of labour, communication, and information asymmetry (Ng & Wakenshaw, 2017). SME owners typically have to rely on numerous field personnel to gather data and engage with clients to learn about their wants and expectations. These statistics only cover a limited period and are sometimes subjective, making them expensive to access and update. However, the incorporation of IoT systems was found to accelerate the collection of real-time and high-quality data from targeted customers.

By automatically sending real-time, high-quality data back to business owners, IoT product platforms help to resolve that problem by eliminating the need for specialists’ involvement thus reducing data costs and leading to profit maximization. Based on the positive correlation between these two aspects, it is evident that an organization’s IoT culture directly affects its financial performance, which can be typically assessed by the return on sales growth rate. This makes it possible to evaluate its success using digitalization as a factor as opposed to reviewing its books of original entries.

IoT is Positively Related to SME Growth and Sustainability

This research validated the direct correlation between IoT incorporation, firm growth and sustainability, as indicated in the study’s proposed model. The findings demonstrated that IoT has a significant positive impact on SME financial performance (p = 0.001, gt = 5.86). Digitalized product service optimization increased SMEs’ profitability and market value. This result is consistent with empirical research on “Servitization through Open Service Innovation in Family Firms” by Rondi, De Massis, and Kraus, (2021). The authors concluded that providing digitalized services had an impact on both the firm’s bottom and top lines in terms of net profit and return on capital employed (ROCE). Similarly, according to Schiavone et al., (2022), there is a favourable correlation between the introduction of IoT and the general sustainability performance, thus providing additional evidence for this association.

On the other hand, IoT-induced sustainability—which is directly related to a firm’s ability to grow—had a correlative bearing on digitalization. According to the findings, digitalization significantly and favourably impacted SMEs’ sustainability performance (r= 0.439, t = 4.03, p>0.001). The association can be justified by the IoT ecosystem’s potential for social, economic, and environmental sustainability as a result of digitalization. This was accomplished by SMEs partnering with other NGOs, offering free training to employees, encouraging plastic-free initiatives, conducting tree planting sessions, and non-renewable resource conservation. According to this study’s finding, SMEs were found to comfortably adapt these practices as they had surplus investment revenue generated from IoT-driven production.

On the other hand, SMEs can change their business models to include more IoT-related digital incentives that alter consumer preferences. For example, increasing the amount of analytical, prognostic, and remote monitoring contributed to the development of new business models and value propositions and was found to significantly improve the financial performance of a firm. This result is consistent with a study by Zemlyak, Gusarova & Khromenkova, (2022) which indicated that technological change and digitalization have an impact on the servitization and profitability of small and medium-sized enterprises. The two factors (digitalization and the internet of things) were identified as enablers of servitization that improved the profit-to-loss ratio of many small businesses (Paschou et al., 2018). This in turn enhanced the overall financial ranking of the business thus further validating this relationship.

The sustainability paradox has become a critical issue that many scholars are trying to address since the previous findings have not been consistent over time. As Shen, Sun & Ali, (2021) argued, although some SMEs have succeeded in engaging in community-based developmental initiatives, social responsibility calls from the U.K. government and other not-for-profit organizations have continued to spiral. In this research, IoT-aided digitalization is proposed to improve a firm’s sustainability efforts, which in turn contributes to the growth of firm performance as it faces less resistance from the general public.

Although this facet was not studied separately in this study, data analysis for the large-scale survey shows that IoT has a positive impact (β =1.0984) on sustainability and this relationship is statistically significant (p ≥0.001). This result confirms observations made by Witell, (2021), which stated that SMEs can initiate eco-friendlier, energy-saving, and resource-efficient programs focused on reusability, social responsibility, innovation, and long-term planning using the current technology. This result, then, suggests that IoT-driven digitalization would be the best route that SMEs can follow to overcome their sustainability paradox and achieve ethical goals.

Moderation Model

Government Interventions Moderate the Relationship between IoT Incorporation and Firm Performance

The government has been identified as one of the main players in the dynamic macro-environment that has a remarkable impact on the relationship between rapid innovation, product service diversification, supply chain efficiency, and firm financial performance. Over the last five years, this hypothesis has received considerable research attention in IoT-related studies authored by Naik et al. (2020), Paiola (2018), and Kolagar et al. (2021). These authors identified it as the largest external player that has the potential to affect aggregate demand, supplier capabilities, market competition, and digital servitization culture. It can introduce policies and regulations that influence consumer and investor saving and spending habits. For instance, imposing bans and sanctions on the use of certain digital avenues affects the performance of SMEs in the respective sector whereas initiating the development of new technology programs promotes IoT growth.

The company’s overall performance is compromised when a sector is subjected to more taxes or tariffs than necessary, which causes the business owners to lose interest in that area. Similarly, tax holidays on a particular sector trigger investment in it and may generate growth leading to improved firm performance. Interest rates are influenced by government policies, and when they rise, the cost of borrowing for businesses increases. As these rates increase, consumers spend less because of reduced disposable income. On the other hand, firms experience remarkable capital deficits hence unable to support their digitalization and innovation goals. Lower interest rates, however, magnifies firms’ capital base leading to increased production and IoT engagement.

This study employed the multi-group analysis in IBM AMOS 25 to examine the moderating impact of governmental policies on the link between innovation and supply chain efficiency on business performance. The Government Intervention (GI) variable was first modified into a category parameter using an average split, where “0” stands for values that are below the median and “1” for values above it. The overall test revealed a statistically significant difference (p<0.002) between the two groups, indicating that the model varies between the two dependent variables. Additionally, the SPSS 25 test showed a positive correlation between the two variables although not statistically significant (p>0.1), while the negative relationship between GI and firm performance was shown to be statistically significant (β = -0.420, p<0.01) for most firms. This result gives deeper insight into why a majority of government intervention measures (policies) will always impact negatively on business performance (Suleiman et al., 2022). Although it is obvious that product service diversification improves business performance, customers might not demand new products regularly when high taxation and interest rates policies are implemented. As a result, if manufacturers continually introduced new products, they are less likely to sell a significant proportion thus leading to subpar firm performance. This concept is adequately ascertained by the study results stated earlier.

These results suggest that whereas governments formulate a variety of laws and policies to guide enterprises, most of them have either a direct or indirect impact on their performance. The interventions can either accelerate or slow down a firm’s interest to incorporate IoT features and servitization models. Whereas the moderating impact of government intervention (GI) on the correlation between GI and supply chain performance was not statistically significant, there exist subtler impacts that the former has on the logistics processes of the supply chain.

Further Research Analysis

The statistical evidence from this study suggests that SMEs can comfortably use IoT as an enhancer for growth and improved performance. Digital servitization and data-driven operations can enhance different facets of operation and aid in the identification of more effective marketing opportunities. A firm’s experience with IoT may be more centred if it is based on current accurate data from its customers (Motohashi & Rammer, 2020). Similarly, firms can maximise both their profitability and customer satisfaction using different IoT features (Paschou et al., 2018). Different study findings confirmed that adopting systemic digitalization constructs (based on IoT-based technologies) is crucial in allowing servitization and can enhance firms’ expansion efforts.

Effective approaches to be used when defining the digitalization conundrum facing the SME industry can facilitate the shift to a more digitalized service business model. To improve the cohesion between programs for digitization and servitization, the findings underlined the need for capitalizing on the firm’s digitalization competencies. The study’s participants, on the other hand, confirmed that the crucial elements of strategic IoT investment were firm resources, supply chain constructs, and servitization competencies.

A firm’s service and digitization processes depend on the strategic digital resource allotment. More significantly, management needs to regularly compare the development of IoT culture within their organizations to key performance measures and previously defined digital incentives (Sironi et al., 2021). The entire idea of digitalization, including servitization conception and execution, is a sequential process, as previously highlighted in the literature review. Therefore, IoT, digitalization, and servitization drivers should be integrated to accelerate businesses toward desirable performance outcomes. To ensure stronger fiscal viability and achieve a significant possibility for capital growth, the use of rationed IoT and digitalization constructs is necessary.

This study’s second hypothesis requires supply chain managers of SMEs to shift their management techniques from employees performing different organisational routines to information and analytics tools in the business. This would ensure that both sides experience a centric network more collaboratively. According to the findings of this study and those compiled by Pham & Vu, (2022), managers of small and medium-sized enterprises must address the interplay of processes and technology to develop supply chains that are more adaptive and steered by digital technology.

The realization that IoT improves the firm’s financial performance, can accelerate growth by providing management with a deeper insight into these essential logistics aspects. This study demonstrated that servitization links business performance and digitalization in five different ways. The value chain from the warehousing phases of inventories to after-sales was reinforced jointly by different IoT features (Raddats, Naik & Bigdeli, 2022). It further emphasized the role that cutting-edge logistics and manufacturing technology play in promoting network collaboration and more regional and flexible supply chains.

Managers need to be aware that the design and deployment of services have a significant impact on IoT drivers. Furthermore, to ensure financial stability and substantial value generation, defined and accurate digitalization and servitization designs are required to achieve the targeted efficiency (Marjanovic, Rakic & Lalic, 2019). To support the serviced business model and productivity improvements, IoT requires a new set of technical capabilities (Truant, Broccardo & Dana, 2021). The product service technology adoption must be viewed as a business project that calls for managerial support and a commitment to servitization and digitalization.

Before these technologies can produce the best outcomes for SMEs, digital servitization frameworks must be connected to appropriate incentives of IoT systems. This is because the majority of commercial incentive constructs focus on a core product line and are always related to digitalized operations (Von Joerg & Carlos, 2022). Finally, the creation of new proactive management tools to examine more IoT-engineered product-service capabilities and their infusion inside the firm may be prompted by the growth benefits and extension of their economies of scale accrued by them.

Digitalization is a critical enabler of successful business performance and can help SMEs realise sustainable value. It offers a framework for integrating sustainability into day-to-day business operations (Formisano et al., 2019). These writers concur that digital servitization and new technologies give organizations a platform to support the application of resource efficiency to their operational processes, which in turn strengthens the overall sustainability emphasis while giving them a competitive edge in the market. According to Tronvoll, Kowalkowski & Sörhammar, (2021), digitalization can change the way product design stages are performed because data that was previously unavailable is now accessible. Similarly, SMEs can leverage it to save data costs, recycle materials, and identify new business opportunities.

Practical Implications of Statistical Data

Cumulatively, the main study’s findings show that technology (IoT) has aided in strengthening the effectiveness of systems, goods, and services. It has been found to assist in managing contacts and employee records, maintaining data flow, and tracking and enhancing customer experience. The operational efficiency of SMEs improved, resulting in cost savings and long-term business expansion. The majority of the SMEs confirmed that digital transformation in SMEs can inspire new ways for them to interact and compete with potential consumers, as well as help them develop new corporate values. Coventry-based firms emphasized that the majority of digital technologies, including big data analytics, machine learning, social media networks, and blockchain systems, can have a significant and advantageous influence on the servitization and sustainability efforts made by SMEs, ultimately leading to an improvement in overall firm performance.

According to the e-commerce business surveyed, the adoption of sophisticated RFID tracking systems gave them unmatched visibility into the supply chain. This facilitated the automation of the shipping and delivery procedures. Concurrently, the fashion production business reported that by using the Internet and its capabilities, they were able to enhance inventory control, save money, and shorten lead times. Customers typically expect openness from the businesses they work with to make purchases. The brewery manufacturing company claims that the adoption of IoT-engineered visibility and traceability throughout the supply chain has considerably contributed to the success of its business. Since its inception, they have been able to win and maintain the loyalty and trust of its customers.

Although domestic & global legislation has increased the complexity of the supply chain for SMEs in the U.K., most of them appraised IoT technology for making it easier for them and their customers to track goods in transit. Additionally, their ability to gather data improved actual output and lowered energy use thus ensuring profitability. SMEs can effortlessly control production operations and equipment performance in real time with the new IoT developments.

Collectively, nearly all SMEs concurred that digital technologies serve as the fundamental building blocks for businesses when they embarked on their digital transformation journeys. They highlighted connectivity to servitization concepts as a critical issue that helped them to reap massive benefits in the long run. Similarly, several SMEs claimed that the adoption of digital transformation should concentrate on how to include developing technologies in the context of diverse business functions toward hybridization, recombination, and inclusivity.

SMEs further concurred that most people do not have absolute confidence in AI-related judgment processes for services like recruiting, financial management, and clinical diagnosis. Some customers had the misconception that machines could take the position of the workers who provide these services, although this has not yet happened. With that in mind, it is preferable to consider AI as a tool for enhancing human intelligence rather than replacing it. As a solution, some managers argued that the leadership of SMEs should reveal that they employ hybrid models. They should highlight the roles that humans and machines play in the firms while enhancing their entrepreneurial orientation. This is due to the general prejudiced customer view of bots and other artificial help tools. Overall, firms concluded that IoT and its features made it easier for newly established firms to take advantage of possibilities and minimise risk.

Conclusions and Recommendations

Summary and Objectives

This study’s main objective is to determine how IoT product systems implemented by SMEs aid in their servitization, financial, and supply chain performance. Various academic works propose digital servitization using IoT to enhance SMEs’ overall performance. However, the majority of studies are theoretical and case-bound. An empirical model that illustrates how IoT product systems might help SMEs to enhance their performance in different areas of digitalization, financial, and supply chain performance has not yet been established and tested by extensive survey-based studies. Thus, the adoption rate is slowed and SMEs are unable to fully leverage IoT’s potential since there is no clear approach for utilizing IoT product systems and their related incentives.

By establishing scientific evidence for the use of IoT incentives to help SMEs in the U.K. to transform into successful product service models and achieve targeted performance, this study addresses the above gap in servitization literature. In chapter three, the study empirically identified essential digitalization capabilities and firm performance aspects. The next goal was then to investigate the IoT and digitalization opportunities that support SMEs and the extent to which these potentials contribute towards enhancing their performance, sustainability, profitability, and growth.

The main research questions that were answered by this study’s results were:

1. Are there ways in which SMEs can theoretically explore different servitization opportunities using available Internet of Things features apart from those already in use?
2. What is the significance of the Internet of Things in key practical business aspects such as supply chain performance and innovation among SMEs?
3. What are the overall outcomes of the use of IoT-engineered digital servitization on SME growth and sustainability?

The two hypotheses postulated in the same chapter were then examined to provide answers to these research questions. The findings of the data analysis showed that all of the hypotheses have statistical validity. A thorough examination of IoT-related literature was conducted via systematic review to find any additional potential digital servitization dimensions to corroborate the initial hypotheses. Managerial, monitoring and automation frameworks were identified and used to build the variables for digitalization constructs. The first question was then addressed by testing the first hypothesis. The results illustrated that the use of IoT digital incentives has a direct effect on a firm’s digitalization performance, implying that more transactional opportunities can be identified and seized on time when these incentives are leveraged.

This finding shows that businesses can utilize IoT devices to digitalize their operations and services. Similarly, the use of IoT systems was found to help to boost businesses’ capacity for digitalization by enabling them to easily monitor, control, and automate their goods, services, and procedures. They further suggest that businesses should make use of IoT product system resources to improve their production capacity while exploring new market opportunities as highlighted in chapter four.

The study model proposes that the intermediaries responsible for enhancing rapid innovation and service diversification include end-user devices and user interfaces, sensor components, and the IoT Cloud. It was necessary to establish these digitalization components based on a variety of prior servitization studies, and then test them using hypothesis four. The results showed that improving a firm’s digitalization receptors has a positive impact on both servitization and new product performance. This finding reinforces the significance of having a strong monitoring, managerial, and automation culture, which assists SMEs in recognizing possibilities, benefits, and risks associated with providing new product services to their clients. With this knowledge, SMEs are better prepared to approach new prospects and remain competitive. Similarly, strong digitalization skills would help them accelerate different innovative processes in terms of shortened product development cycles and timely product launches.

When hypotheses two were tested, they revealed a positive correlation to overall business performance. For the case of the supply chain efficiency-the hypothesis that aimed at demystifying confusing concepts in Sisti, Estensoro, and Larrea, (2021) study-the use of automation confirmed the possibility of linking smart devices to one another via M2M communication pathways discussed in chapter three. This feature was found to facilitate consistent and dependable real-time communication between devices in addition to improving access, traceability, adaptability, and agility of the entire supply logistics department. To effectively analyse these correlations, Structural Equation Modelling was used in chapter four alongside AMOS 25, CITC, and Cronbach Alpha multivariate techniques.

Critical Reflections

Firstly, by outlining the IoT incentives and how IoT features can be used as resources to strengthen a firm’s digitalization capacity, this study contributes to the understanding of Digital Engineering and Industry 4.0 concepts. Three IoT-enabled constructs were established based on the existing IoT literature. They include:

1. IoT-enabled automation focuses on supply chain coordination and product service diversification.
2. IoT-enabled connectivity, emphasizes the cohesion provided by IoT technology.
3. IoT-enabled adaptability, which emphasizes IoT flexibility.

All of these constructs have obtained empirical validation and exhibit high model fit, making them essential tools for upcoming IoT research.

Secondly, this research is among the first ones to examine digital servitization from the standpoint of dynamic capability. This resource‐based view can better represent the unique characteristics of digitalization such as data detection, transition, and interpretation capabilities, alongside their usefulness as highlighted in chapter three. There were three aspects identified under the dynamic capacity standpoint namely:

1. Monitoring focuses on a firm’s capacity to detect changes in its operations and supply chain.
2. Managerial, which emphasizes a firm’s capacity to regulate its operations; and
3. Automating emphasizes a firm’s capacity to digitalize its operational procedures.

These concepts demonstrated composite reliability and divergent validity of the study, which is compatible with some hypotheses outlined by (Zemlyak, Gusarova, and Khromenkova, (2022). Future studies can use it to better explore the field’s competency or to keep improving its tools. The third contribution of this paper involves providing a solution to the servitization/production quandary. It supports the findings of several related works of IoT literature by offering several benefits to buffer the vulnerabilities and uncertainties associated with the use of servitization. More significantly, this study explored a potential paradigm for how IoT incorporation can benefit SMEs in key aspects of growth and sustainability.

Future Work and Recommendations

This research has certain shortcomings, despite being thoroughly done by adhering to specified methodologies and study criteria. Its conclusions should therefore be interpreted with caution in light of these limitations. Firstly, the study’s 40 participants constitute a rather small sample size. Although it is quite close to the size suggested by (Zemlyak, Gusarova, and Khromenkova (2022), the generalization of the results would be better with a larger sample size. This is significant because additional observations would improve the sample’s representation of the population and enhance the reproducibility of the findings. Therefore, with a larger sample size in future studies, the hypotheses discussed herein might be revisited in future studies and findings improved.

Secondly, there was only one respondent who was required to answer the questionnaire from each firm. Since the respondent was questioned about digital practices and performance independently, there could have been a respondent’s bias. Multiple respondents from each organization can be used in future studies to verify the findings discussed herein. On the same note, it’s crucial to have extremely specific criteria for selecting the sample, particularly when using a third-party platform like Jisc to gather respondents, so that the ineligible ones can be eliminated. Future studies should thoughtfully include both open-ended and closed-ended questions to select the most appropriate participants.

Thirdly, small businesses accounted for the minority of respondents in this study (22.5%), while medium-sized businesses accounted for 77.5% of respondents. Given the high cost of IoT product systems and the resources required for venturing into the IoT niche, the results may be biased because medium and big enterprises are more likely to embrace digitalization due to their heavier capital base. Future research may solve this issue by surveying a fifty-fifty proportion to validate the research paradigm presented in this study.

Conclusion

The first chapter provided a background of the research topic by outlining different constructs of IoT and digital servitization and how they affect business performance. The second chapter concluded that IoT had positive impacts on aspects such as supply chain, product innovation and financial performance through a comprehensive systematic literature review. The third chapter concluded that the research was to be conducted in two ways namely, an online pilot survey and a large-scale study. The Research Onion was introduced to guide the study’s methodology. The fourth chapter found that all the hypotheses were statistically significant and hence each of them answered its respective objective from which it was derived. This chapter marked the end of the study by giving the research’s contributions to this topic, outlining some study limitations, and providing recommendations for further research in this niche.

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Appendices

Appendix 1. Gantt Chart

Appendix 2: Open-ended Questionnaire Sample

Questionnaire on the Impact of IoT on Digital Servitization and Business Performance among SMEs

Section 1. (Conditional Questions)

1. Since its inception, has the Internet and its features affected your business’s automation process? If yes, list the two main ways.
2. Has the new Artificial Intelligence system enhanced your business’s capacity to increase productivity? If so, to what degree have the preexisting products been diversified into new ones?
3. Do you think small and medium-sized enterprises can automate coordination within departments and facilitate the flow of vital information using the new technology? If so, how?

Section 2. (General Questions)

1. Identify any 3 community-centric services that your business has provided before and after the adoption of new technology in the past 12 months
2. Provide any two new ways that your business could use the Internet of Things capabilities to find new digitalized production opportunities.
3. How has the Internet and its features affected the efficiency of your company’s supply chain?
4. How has the adoption of digitalized production methods (engineered by the Internet and its features) affected the expansion and sustainability of your business in general?
5. Verify whether or not the adoption of the Internet and its features has been the primary catalyst for rapid innovations in your business.
6. Instead of using the standard journal-ledger auditing approach, highlight the possibility of assessing your business’ financial performance throughout a financial year by evaluating its level of use of technology in production.

Appendix 3. Likert Scale Questionnaire

Likert Scale Questionnaire on the Impact of IoT on Digital Servitization and Business Performance among SMEs

Appendix 4: Participant Information Statement

Participant Information Statement

Impact of IoT Technology on Digital Servitization and Business Performance of SMEs

The purpose of the research is to establish the significance of use of IoT tools in product diversification, innovation and servitization among SMEs.

The research project is being conducted by Napat Chaipatananant at Coventry University. You have been selected to take part in this questionnaire survey because you are senior-level employees or marketing and operational managers. Your participation in the survey is entirely voluntary, and you can opt out at any stage by closing and exiting the browser. If you are happy to take part, please answer the following questions relating to probes the influence of IoT incorporation by SMEs on their servitization culture, supply chain, growth, and sustainability aspects used to gauge business performance. Your answers will help us to understand the use of IoT engineered digital servitization on SME growth and sustainability. The survey should take approximately 30 minutes to complete.

Your answers will be treated confidentially and the information you provide will be kept anonymous in any research outputs/publications (where it will be used only in anonymised or aggregated form). Your data will be held securely on the University secured OneDrive. All data will be deleted by 1 December 2022.

The research was granted ethical approval by Coventry University’s Research Ethics Committee P140324.

For further information, or if you have any queries, please contact the lead researcher Napat Chaipatananant +447562494416. If you have any concerns that cannot be resolved through the lead researcher or supervisor, please contact [email protected].

Thank you for taking the time to participate in this survey. Your help is very much appreciated.

• I have read and understood the above information.
• I understand that, because my answers will be fully anonymised, it will not be possible to withdraw them from the research once I have completed the survey.
• I confirm that I am aged 18 or over.
• I agree to take part in this questionnaire survey.

Appendix 5: Ethics Certificate

Glossary

• IoT – Internet of Things
• SMEs – Small and Medium-sized Enterprises
• I.T. – Information Technology
• SPSS -Statistical Package for the Social Sciences
• M2M – Machine to Machine
• AMOS -Analysis of a Moment Structures
• SEM -Structural Equation Modelling
• U.K. -United Kingdom
• RFID – Radio-Frequency Identification
• AI – Artificial Intelligence
• JISC – Joint Information Systems Committee Online Survey
• CSP – Cloud Solution Provider

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