Introduction

Small- and medium-sized enterprises (SMEs) are considered major contributors to a country's economic development, due to their ability to boost its productivity and living standards (Akingunola, 2011). According to Schumpeter (1935), SMEs are the primary source of entrepreneurship, innovation and technical progress, as well as key suppliers of human resources and raw materials to larger corporations. Sunusi (2002) observed that SMEs are the key engines of economic development, pillars of creativity and innovation and incubators of entrepreneurship, accounting for more than half of emerging countries' GDP. World Bank (2002) in their study observed that SME operations are labour-intensive and have a stronger capacity to create more jobs, easily adjust to changes because of their smaller size, and are more productive than huge corporations. According to Zubair (2014), SMEs can improve competition and entrepreneurial growth in less developed nations, due to economic efficiency, innovation and aggregate productivity development and are more efficient than large enterprises. As they run on shoestring budgets, they are more innovative, and entrepreneurially driven, but fragile, and are ‘distress-pushed’ (Ahmed, 2016). Because of their smallness and agility, they are more adaptable to cutting-edge technologies than large-scale industries. Despite the potential benefits of digital technology, SMEs are hesitant to embrace digital innovation or fail to reap the benefits of new technologies.

Various studies have investigated the individual, technological, organisational and environmental factors that influence digital technology adoption, and the results associated with it. This paper tries to analyse the theoretical contributions made by various scholars concerning the development of SMEs in the areas of entrepreneurship, technology, clustering and networking, internationalisation, the resource-based view, institutional theory, stakeholders' and agency theory, pecking-order theory and life-cycle–based theories for the understanding of adoption process of technologies and determinants of growth in SMEs. This will give a bird's eye view of frequently applied theories developed over years and will be extremely useful for upcoming researchers.

This article is categorised into four major sections. The next section examines the evolution of scholarly literature on SMEs. Various classical theories were discussed in the subsequent section, while the last section and its sub-sections focus on modern theories, analysing technological theories, stakeholders’ theories and life-cycle theories.

Evolution of Academic Literature on SMEs

Various researchers have contributed a lot in the area of serious academic research in the field of SMEs and formulated various theories. Filley et al. (1976) defined a theory as ‘an efficient mechanism for abstracting, codifying, summarizing, integrating, and classifying information’. Theories surrounding SMEs include the leadership qualities of an entrepreneur, variables that the entrepreneur can comprehend, influence and evaluate for the adoption of technologies, innovations, financial grievances and the behaviour of people working in a firm, focusing specifically on ethical behaviour (d’Amboise & Muldowney, 1988). Theories act as guideposts, indicating what is significant, why it is important, what determines this importance and what we should expect as a result. The research that is based on them can provide a fair evaluation of the data and any inconsistency might lead to inconclusive results. Authors while investigating new situations can add a new set of assumptions by revising the initial assumptions to arrive at new theoretical conclusions. Various academicians have developed several management theories, which are beneficial for the growth of SMEs and are categorised into two major divisions: classical and modern theories.

Classical Organisation Theories

Classical theories were based on the literary works of Schumpeter (1942), Hoselitz (1959), Staley and Richard (1965), Kirzner (1999), etc. Classical theories emphasised the impersonal and rational nature of organisations, regulated by hierarchical levels of authority (Shafritz et al., 2005). In their study, Staley and Richard (1965) observed the predominance of SMEs in the least developed countries either due to the location of raw materials or the availability of cheap labour.

Hoselitz (1959), in his study on German industrialisation, noticed how smaller firms in the manufacturing sector later expanded into large-scale industrial institutions. He observed that low manufacturing costs were the key to SMEs' success. Parker (1979) and Khambata and Anderson (1981) expanded their works to study various developmental phases of SMEs and their transition from small enterprises to medium, and large enterprises. According to classical theories, huge firms will take over smaller firms as the economy progresses, to increase their revenues, making the SMEs gradually fade away (Onakoya et al., 2013).

The economists, philosophers and policymakers of the post-war century, such as Schumpeter (1935) and Galbraith (1967), were more confident of the development in the hands of huge corporations rather than by small enterprises and were convinced that they would eventually fade away because of their inefficiencies in the future. Schumpeter (1942) focused on the importance of huge corporations, which act as economic growth engines, through their non-transferable knowledge in certain technological sectors and markets. Schumpeter's (1942) growth theory focused on entrepreneurs, innovations and long waves, ‘creative destructions’ played by a dynamic entrepreneur, or massive research by R&D-based corporations, which act as driving factors behind structural and radical changes. According to Penrose (1959), large corporations are more capable of influencing their environments than smaller ones, as they have better resource positions. According to Penrose (1959), huge corporations may not want to eliminate smaller competitors, as they produce small supplementary items that are not cost-effective for them to manufacture.

Modern Organisational Theories

Since the 1980s, there has been great growth in technological advances, innovations and changes in entrepreneurial activities all over the world as a result of globalisation. This resulted in the emergence of a significant amount of literature on entrepreneurship, innovation and technology (McAfee & Brynjolfsson, 2008). As such modern theories focused more on the importance of entrepreneurial talents, innovative skills, digitalisation of the firms, network subcontracting, economic benefits of agglomeration and clustering for the development of SMEs.

Entrepreneur–Innovation Theory

Toulouse (1979) defined an entrepreneur as an individual who takes significant risks towards the developmental activities of a company. According to Drucker (2014), innovation is a specialised tool used by entrepreneurs to bring changes in organisations or various services through the installation of new types of equipment, and cutting-edge products, to improve the efficiency of services and product quality. Innovations aid in increasing productivity, creating jobs, generating income, improving infrastructure and aiding in ease of living (Laforet, 2013). They provide improvised goods and services, with the assistance of efficient technologies, timely availability of financial resources and highly qualified personnel (O’Sullivan & Dooley, 2008). Hessels and Terjesen (2008) observed that higher degrees of entrepreneurial skills are positively corelated to the exporting by companies.

Kirton–Adaptation–Innovation Theory

Kirton (1976) proposed the Kirton–Adaptation–Innovation (KAI) theory of bipolar concept, which focused on improvising, less disruptive and more readily acceptable ideas, or path-breaking, transformative, more disruptive and less readily acceptable ideas at the other end of the paradigm. Garcia and Calantone (2002) identified that radical innovations enable SME owners to use new technology, resulting in new market infrastructure, generating previously unidentified consumer demand, to stay ahead of the competition. While incremental innovations fine-tune and improvise the existing technology by adding additional features, benefits, or enhancements to existing products (Garcia & Calantone, 2002).

Upper-echelons Theory

The upper-echelons theory (also referred to as the ‘top management team’ theory) was proposed by Hambrick and Mason (1984). It asserts that the managerial attributes of the top management determine the organisational outcomes. The upper-echelons theory is crucial since upper executives play a critical role in promoting organisational effectiveness (Hambrick, 2007). According to Hambrick and Mason (1984), entrepreneur education, organisational size, type and location, strategic decision-making, governmental support, vendor support, customer pressure and R&D are usually considered antecedents for SME growth (Tödtling & Trippl, 2005). SME owner characteristics include improved decision-making abilities, and an entrepreneurial mindset, which leads to increased levels of competitiveness, growth and profitability among exporters (Kazem & Van der Heijden, 2006).

Technological Theories

In a mature market, to attain a competitive advantage, SMEs should continuously upgrade their systems for a leaner, agile and more efficient approach. According to Prananto et al. (2002), the rise of the internet has created a valuable opportunity for small businesses to reach out to new markets and increase customer satisfaction. Hamilton and Bowers (2006) and Earl (2006) regarded the internet as a tool for lowering costs, increasing efficiency, exapanding the market and making social change, resulting in revenue improvement.

Since the 1990s, researchers focused more on studying digital technology adoption like computerisation and computer-based information systems by SMEs. In the 2000s, digital technologies such as ICT, the internet, websites, e-commerce, e-business and enterprise systems were widely adopted. This was followed by the adoption of cloud computing and knowledge management systems, social media adoption, etc., in the 2010s. The period 2015–2023 saw the emergence of new digital technologies such as Industry 4.0, blockchain technologies, drones, 5G technologies and sustainability in supply chains.

Numerous scholars have developed various technology adoption models to understand and verify the impact of the entrepreneur–technology–innovation paradigm, on SMEs' growth and development.

Diffusion of Innovations Theory

The theory of diffusion of innovations (DOI) is the oldest social science theory developed by Rogers (1962), for describing the acceptance or rejection of new technologies. Rogers identifies diffusion as ‘a process to how quickly the innovation can be embraced by the members’. DOI theory can be seen more at the corporate level rather than at the operational level, according to Oliveira and Martins (2011). Figure 1 given below shows the influence of various constructs on the adoption of innovation as posited by Rogers (1995).

Rogers' diffusion model is represented through an innovation–adoption curve, where the population is categorised on risk aversion and risk propensity. They are segregated into innovators, early adopters, early majority, late majority and laggards. Rogers' theory is widely used in the theoretical framework for technology adoption and innovation diffusion and posits five attributes relative advantage, complexity, compatibility, trialability and observability to business intelligence to analyse the technological innovation adoption in SMEs (Boonsiritomachai et al., 2014).

Theory of Reasoned Action

Fishbein and Ajzen (1975), in their ‘theory of reasoned action (TRA)’, attempted to explain a user’s intention to perform a behaviour (behavioural intention) through: (i) his attitude towards the behaviour and (ii) subjective norms regarding the behaviour. Behaviour is characterised by one's attitude towards it, and subjective norms refer to perceived social pressures from peers and family. According to Fishbein and Ajzen (1975), the acceptance of technology or its rejection, depends upon the perceived benefits to the user, or in its difficulty to understand or utilise it. Based on seven causative variables, the model shown in the Figure 2 predicts behaviour: behavioural intention, attitude, subjective norm, belief strength, evaluation, normative belief and incentive to comply (Liska, 1984).

Several scholars have used TRA theory to understand the behaviour intention towards brand loyalty (Ha, 1998) and green behaviour (Gotch & Hall, 2004) to study specific types of behaviours such as consumer behaviour (Fitzmaurice, 2005), green behaviour (Mishra et al., 2014) and predicting health behaviour (Gillmore et al., 2002; Godin & Kok, 1996) and for planning and implementing health promotion and disease prevention programmes.

Theory of Planned Behaviour

The theory of planned behaviour (TPB) developed by Ajzen (1991) is an extension of the TRA of Ajzen and Fishbein (1975) to overcome the flaws of TRA's behavioural intentions (Ajzen 1991). TPB was expanded further by introducing perceived behavioural control (PBC), based on Bandura's (1986) concept of self-efficacy. Self-efficacy is a person's expectation or confidence in his or her ability to master a behaviour or achieve a goal (Bandura's 1986).

Behavioural intention (BI) refers to ‘an individual's willingness to perform a specific behavioural action, which is influenced by three important elements, perceived behavioural control, subjective norm, and behavioural attitude’ (Ajzen, 1991). PBC refers to users’ belief that he or she can do a behaviour of interest with ease or difficulty. We summarize the TPB framework in Figure 3.

TPB model is used in various healthcare studies to predict behaviour change theories, which include habitual smoking (Karimy et al., 2015), alcohol addiction (Cooke et al., 2016), family planning, health services utilisation (Javadi et al., 2013), patient safety (Javadi et al., 2013) and studies on breastfeeding, sex worker's safety, among others.

Technology Acceptance Model

Davis (1989) established the TAM, based on the TRA, which deals extensively with predicting the degree of IS adoption at the individual level and determining user acceptance (Surendran 2012). According to Agarwal and Prasad (1999), TAM is the most commonly used model to understand the intention for IS acceptance. The term ‘perceived usefulness (PU)’ was coined by Davis (1989), to define ‘the degree to which a person believes that using a specific system will improve his job performance’ and ‘Perceived Ease of Use (PEOU)’ to define ‘the degree to which a person believes that using a particular system will be effortless’. According to Davis (1989), user attitude is directly affected by PU and PEOU. The TAM model was further extended by taking into consideration of external variables, which might influence the user's belief towards system usage. Figure 4 investigates the variables that influence the behaviour intention.

TAM theory was expanded on the concept of TRA to better comprehend customer behaviour, attitudes and intentions towards emerging technologies. It is frequently used in e-commerce adoption, e-learning adoption (Hsbollah et al., 2009), internet banking (Radomir & Nistor, 2013), mobile banking (Ahmad, 2018), etc. The TAM model was widely criticised for failing to provide sufficient insights into people's perceptions of innovative systems.

TAM-TPB Model

Taylor and Todd (1995) combined TAM and TPB theories to create the TAM-TPB model, which included predictor variables like attitude towards behaviour, subjective norms derived from TRA/TPB, PBC and PU derived from TPB. Figure 5 gives a detailed view of integrated TAM-TPB model.

Technology Acceptance Model 2

The TAM 2 model was proposed by Venkatesh and Davis (2000) to improvise the TAM1 model for IS adoption. They tried to integrate social influence processes such as subjective norm, experience, perceived voluntariness (the extent to which potential users intend to adopt new technologies) and image (how the usage of innovation can improve one’s status), with cognitive instrumental processes, like job relevance (the extent to which the innovation can improve the job performance), output quality (refers to an individual’s perception of how well the system performs to complete specific tasks), result demonstrability (refers to usage results that can affect the system’s usefulness) and PEOU. Figure 6 looks into the various constructs that influence individual’s usage behavoiur as proposed by Venkatesh and Davis (2000).

According to Venkatesh and Davis (2000), TAM2 favours all cognitive instrumental processes that favourably influence PU, which results in an individual's propensity to adopt an IS.

Technology, Organisation and Environment Framework

Tornatzky et al. (1990) introduced the technology, organization and environment (TOE) paradigm, which highlights the three aspects that impact an organisation’s intention to adopt and use technological innovations. The technological context refers to the adoption of both internal and external technologies concerning the firm. Organisational context measures the top management support, availability of skilled employees and cost benefits. Environmental context considers facilitators and inhibitors for firm growth like competitive pressure, government support and sustainability. According to Oliveira and Martins (2011), the TOE model is frequently used in IT adoption studies to provide a framework for assessing the acceptability and assimilation of IT innovations. Figure 7 summaries the technological, organisational and environmental factors that influence the TOE framework.

Awa et al. (2017) extended the TOE’s insights by combining task–technology–fit and UTAUT frameworks, to investigate higher-level attributes, instead of the ease-of-use behaviour of individuals in the organisation.

Unified Theory of Acceptance and Use of Technology

Venkatesh et al. (2003) combined key features from eight behaviour intention theories and models to predict or explain a person’s BI to use technology to form the unified theory of acceptance and use of technology (UTUAT) model. After a thorough review of the literature, he combined the TRA (Davis 1989), the innovation diffusion theory (Rogers, 1995), the TPB (Ajzen 1991), the TAM (Davis, 1989), the combined TAM-TPB (Taylor & Todd, 1995), the motivational model (Vallerand, 1997), the model of PC utilisation (Thompson et al., 1991), and ssocial cognitive theory (Bandura, 1986) theories into the UTUAT model to explain IS usage behaviour.

The four key dimensions, such as performance expectancy (PE), effort expectancy (EE), social influence (SI) and facilitating conditions, were included to determine BI to understand how to use an IS, and its usage behaviour, varying with gender, age, experience and voluntariness to use, to moderate the impact of usage intention and behaviour (Venkatesh et al., 2003). PE, as defined by Venkatesh and Davis (2003), is 'the degree to which an individual perceives the system that aids in boosting work performance', while EE is ‘ease with which an individual gets linked with the utilisation of the system’. PE, EE and SI all have a significant impact on users' behaviour intention in adopting new technologies. Figure 8 shows the four constructs and four moderators that influence the behavioural intention and predicting the usage intention of new technology by an individual.

Several academicians have studied the UTAUT model in depth to understand and explain the behaviour intentions towards the acceptance and utilisation of new technology. Some of them are mobile health adoption (Hoque & Sorwar, 2017), enterprise resource planning (ERP) (Keong et al., 2012) and software acceptance in SMEs (Chauhan & Jaiswal, 2016), etc.

UTAUT 2 Model

Venkatesh et al. (2012) extended the UTAUT 1 model to investigate the technological acceptance preferences of an individual, by adding three new drivers of intention, like hedonic incentive, price value and habit into the original model. In the UTAUT 2 paradigm, facilitating condition is the predictor of BI (Venkatesh et al., 2012). Hedonic consumer behaviour was associated with fun, enjoyment and excitement, while the emotional and experiential value of shopping, being more subjective and personal was attached to the hedonic value. Figure 9 predicts the technology acceptance using seven extended drivers of adoption intention as proposed in UTUAT2 model.

Several IS/IT studies have used some or all of the UTAUT2 (Venkatesh et al., 2012) constructs, like in the use of learning management systems (Ain et al., 2015), consumer acceptance of e-governance technology (Krishnaraju et al., 2013), availability of internet facilities to the residents of a city (LaRose et al., 2012), etc.

Networking and Clustering Approach

‘Networking’, as defined by Lechner et al. (2006), is a relationship between people or organisations that can serve a variety of purposes, while agglomeration of the interconnected enterprises and related firms is referred to as ‘Clustering’ (Ceglie & Dini, 1999). Figure 10 summarises the concept of networking theory.

The term ‘network’ refers to partnerships between businesses that work together to achieve a common economic goal by developing close relations with customers, thereby complementing, and specialising to address mutual difficulties, to win markets that would have been too tough for them to reach on their own. Clusters are geographical and sectoral groups of enterprises that produce and sell a wide range of related or complementary goods and services and face similar challenges and opportunities. Several ancillary institutions, such as business-related organisations and technical or training service providers, are located near the clusters (Ceglie & Dini, 1999).

‘Clusters’ foster the development of value chains, private and public institutions, enhancing differentiation, which supports the local economic growth for specific raw materials, suppliers and the development of specific skill sets, which increases profitability (Humphrey & Schmitz, 1995). Networking activities assist in expanding businesses to gather resources for new endeavours, yet maintaining their flexibility (Demirgil et al., 2011). Networking can assist firms in overcoming constraints by allowing them to form ties with established businesses and reduce risk (Madhok, 1997). Networking can help SMEs compete on a global scale, by allowing them to form ‘symbiotic’ ties with larger companies Etemad (2004), while clustering of firms can assist in framing favourable governmental policies, which support regional or local economic development (Ceglie & Dini, 1999).

Ritter et al. (2002) emphasised that firms should not be considered in isolation but should be viewed as interconnected bodies. For SMEs with limited resources, clustering and networking ties can be useful in the establishment of collaborations with diverse stakeholders. Networking and clustering can be powerful tools for poverty elimination, for getting resources and opportunities and for motivating the growth of competing industries and the expansion of SMEs to venture into international markets.

Internationalisation Theory

Simmonds and Smith (1968) observed internationalisation as a significant variable for small businesses, resulting in a firm's growth, due to the aggressive and competitive nature, high-risk tolerance and export behaviour of an individual. Entrepreneurial talents, according to Hessels and Terjesen (2008), are positively associated with a company’s exports. Pickernell et al. (2011) observed that graduate entrepreneurs are better export-oriented, and inclined towards the internationalisation of the firm than non-graduate owners, despite having no prior experience of owning/managing a business. According to Buckley and Casson (1998), internalisation allows businesses to expand their activities worldwide through the vertical integration of their operations.

Dunning (1988) identified three benefits: (i) internationalisation benefits that a firm can achieve through its ability to organise and coordinate its operations; (ii) geographical or locational advantage of an institution; and (iii) advantage gained through the accumulation of intangible assets. According to Kazem and van der Heijden (2006), exporters improved their decision-making abilities by improving their entrepreneurial orientation, resulting in more competitiveness, growth and profitability than non-exporters.

Institutional Theory

Institutional theory refers to the innovative elements associated with long-term growth of SMEs that inspire management to achieve their goals through cultural, legal, social, environmental, traditional or cultural and economic variables (Srisathan et al., 2020). The institutional setting influences the company’s international behaviour, by supporting or hindering the process of internationalisation (Rutashobya & Jaensson, 2004).

Institutional network links can affect market selection and entry strategies, help lower costs and risks, provide access to established channels, increase credibility and can motivate internationalisation (Zain & Ng, 2006). Institutional theory affects the selection of variables that influence environmental, social and economic decision-making. An increasing number of SMEs throughout the world are aiming for sustainable business methods, which promise profit, resilience and social and environmental consequences (Caldera et al., 2017).

Resource-based Theory

A resource of a firm is considered as ‘Everything that could be a firm's strength or weakness’. Gottschalk (2007) defines resources as ‘tangible and intangible assets that have been linked to a firm for a long time’. According to Penrose (1959), a company derives its competitive advantage, through the use of its internal resources, i.e., its valuable tangible and intangible resources. According to Nguyen et al. (2008), resource-based theory gives guidelines to businesses on how to identify appropriate measures, overcome growth barriers, gain better access to technology, personnel, financial resources, natural resources and infrastructure, as well as market access. According to Rindova and Fombrun (1999), the resources, capabilities and core competencies of a firm pave the way for its competitive advantage in the marketplace. The resources, talents and core competences of a corporation pave the way for its competitive advantage in the marketplace (Rindova & Fombrun, 1999). Barney (1991) investigated how resources affect a single-business firm's performance. According to Grant (1991), four types of tangible resources influence a firm's success, financial, organisational, physical and technological resources, as well as three types of intangible resources: people, innovation and reputation of the firm's performance. As part of the VRIO paradigm, Barney and Wright (1998) established four resource attributes: (i) value, (ii) rarity, (iii) imitability and (iv) operability. The classification of resources that enhance a company’s competice advantage are shown in the Figure 11.

Barney (2001) extended the VRIO framework by expanding operability with substitutability, combination and exploration and making it into six. Wade and Hulland (2004) reconstructed value, rarity, appropriability, imitability, sustainability and mobility as six attributes of a company's resources. They observed that some resources provide a competitive edge, while others assist in their maintenance. Gottschalk (2007) identified value, rarity, exploitability, imitability, substitutability, combination and mobility as the seven criteria to determine the level of competitive advantage provided by resources. Caldeira (1998) used RBV theory to understand how businesses achieve a long-term competitive edge and outstanding performance.

Many academicians investigated the relationship between IT resources and company performance. Many studies categorised IS resources into technology-based IS assets (infrastructure) and capability-based IS assets (systems-based).

Stakeholders’ Theory

Stakeholders, according to Stanford Research Institute (1963), are ‘those groups on which the organisation depends for its continued survival’. Freeman (1984) redefined stakeholders ‘as a group or individual, who can influence or be influenced by the achievement of the firm’s objectives’. According to Parmar et al. (2010), when the interests of stakeholder’s collide, the entrepreneur strives to meet the demands of the stakeholders by giving benefit to each stakeholder. If trade-offs are to be made, then executives must first figure out how to improvise the situation for all parties (Freeman et al., 2008). Figure 12 shows the influence of various stakeholders on the performance of the firm.

Agency and Stakeholders Theory

Agency theory describes the relation between business owners and agents and aims to solve conflicts from a behavioural and structural perspective. Donaldson and Davis (1991) developed stewardship theory as a counterpart to agency theory to explain the relationship between firm ownership and management. Managers have a moral obligation, in accordance with stewardship theory, to maximise the company's revenue and offer decent returns to stockholders (Davis et al., 1997). In the principal–steward relationship, a steward prioritises the principal's interests over self-serving interests, whereas agents prefer opportunistic self-interested behaviour over optimising the principal's benefit (Davis et al., 1997). Agency theory, according to Chrisman et al. (2004), tries to explore specific difficulties of family firms, whereas stewardship theory, according to Davis et al. (1997), is primarily concerned with governance in the family business environment. The objective of stakeholder theory is to provide value to each stakeholder, whereas stewardship theory focuses on the organisation's long-term interests.

Pecking-order Theory and Trade-off Theory

The theory of the pecking order addresses the immediate needs of a firm’s funding and provides a rational explanation for the choice. Myers (1984) proposed the pecking-order theory to explain the firm's preference for internal funds over external ones, as well as its preference for debt issue over equity issuance. According to pecking-order theory, corporations do not have an optimal capital structure, but rather prefer a mix of funds based on manager preferences and the cost of each capital source. While the optimal capital structure is supported by the trade-off theory (Litzenberger & Kraus, 1973), which focuses on lowering the firm's weighted average cost of capital while optimising its value (Byoun, 2008). Banga and Gupta (2017) examined the capital structure of 64 small- and medium-sized businesses in India from 2007 to 2012 and observed that both theories complement each other.

Figure 1. Diffusion of Innovations (DOI) Model.

Source: Rogers (1995).

 

Figure 2. Thsseory of Reasonable Action (TRA).

Source: Fishbein and Ajzen (1975).

 

Figure 3. Theory of Planned Behaviour (TPB).

Source: Ajzen (1991).

 

Figure 4. Technology Acceptance Model.

Source: Davis (1989).

 

Figure 5. TAM-TPB Model.

Source: Taylor and Todd (1995).

 

Figure 6. The TAM2 Model.

Source: Venkatesh and Davis (2000).

 

Figure 7. The TOE Framework.

Source: Tornatzky et al. (1990).

 

Figure 8. Unified Theory of Acceptance and Use of Technology (UTAUT).

Source: Venkatesh et al. (2003).

 

Figure 9. Unified Theory of Acceptance and Use of Technology2 (UTAUT2).

Source: Venkatesh et al. (2012).

 

Figure 10. Networking Theory.

 

Figure 11. Resource-based Theory.

Source: Barney and Wright (1998).

 

Figure 12. Stakeholder Theory.

Source: Freeman (1984).

 

Life-cycle Theory

Greiner (1972) proposed his well-known 'Greiner model' in life-cycle theories, explaining how extended periods of evolution are interrupted by 'revolutions'. Miller & Friesen (1984) figured out that many studies have used a firm's life cycle, as a key area to analyse the dimensions of size, growth and development. According to Kazanjian and Drazin (1990) and Scott and Bruce (1987), growth models act as diagnostic tools, to assess a company's current situation and anticipate its requirement, as they move from one stage to the next in its life cycle. Most of the academic models divide an organisation’s life cycle into four or five stages, ranging from birth/existence/start-up, transiting to survival/early growth, leading to maturity, slowly declining and leading to death/revival with new ventures (Jirasek & Bilek, 2018).

Firms typically start as small and expand as they gain expertise. Smaller and younger firms face more turmoil than their larger counterparts as they grow. SMEs must explore new markets and produce new goods to attain long-term profitability. According to Scott and Bruce (1987), once SMEs start to grow, they either plateau off or enter new stages of expansion, transitioning from a small to a medium or even a large firm. According to Lewis and Churchill (1983), management may develop better strategies for the future, if they have a better awareness of the issues, challenges (present and future) and problems, they may face at each stage.

Conclusion

In a time when globalisation has an impact on both the global and local economies, innovation, technological improvements, resource orientation and networking are critical for SMEs to maintain a competitive advantage. The paper is limited only to a few theories and strategies, that researchers use to study various determinants for the growth of small businesses.

Various theories complement each other, adding rigour and usefulness to developing entrepreneurship research. Extensions of a particular theory can lead to more creative applications of the theory. It can also give policymakers a solid platform to build their strategies for nurturing, supporting and extracting entrepreneurial activities in ways that improve our quality of life. Theoretical understanding will help us gain new perspectives on the academic applicability of the determinants of the growth of SMEs.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Krishna Veni Raparla   https://orcid.org/0000-0002-5454-8763