S-commerce success for SMEs in an emerging economy: a technology-organization-environment-based approach

Abstract

Purpose  This study aims to examine a competency model of social commerce (s-commerce) for small and medium-sized enterprises (SMEs) performance and explores the moderating effect of locus of control on s-commerce success.

Design/methodology/approach  Based on the technology-organization-environment (TOE) framework, the authors collected 414 samples and analyzed them using structural equation modeling.

Findings  The study finds that information and communication technologies, business processing, security and privacy, trust and governmental support each have a significant positive effect on s-commerce success for SMEs. Customer service, organizational culture and support from business partners do not significantly affect s-commerce success. In addition, locus of control strongly moderates the relationships between specific TOE factors – namely, business processing, security, trust and government support – and s-commerce success, either strengthening or weakening these effects depending on the individuals’ locus of control.

Research limitations/implications  The study records data from a single country and looks at SMEs from a variety of industries, thus caution is required to generalize the findings.

Practical implications  This study highlights how emerging technologies drive s-commerce success, especially in boosting revenue and sales through advanced generation and materials.

Social implications  These results highlight the value of s-commerce in the TOE framework for understanding key aspects of SME performance and sustainability.

Originality/value  This study identifies key future research areas for SMEs’ e-commerce, emphasizing digital marketing strategies to guide future research on s-commerce growth.

S-commerce; SMEs; Technology-organization-environment framework; Technology adoption; Organizational cultures; Environmental factors

^1.

Introduction

Many countries, particularly developing ones, are experiencing rapid growth in e-commerce. This growth combines information technologies and new business methods (Ali, Mukhtar, & Mohamed, 2020). E-commerce has become a significant segment of Bangladesh’s economy (Hossain, Hossain, Chowdhury, & Shuvro, 2024). Government agencies work with the e-commerce Association of Bangladesh to boost the sector. The government, businesses and nonprofits all provide support. E-commerce technologies can accelerate economic growth across all industries. ECDB (2024) states that Bangladesh’s e-commerce revenue was US$10,959.5m in 2024, ranking 31st globally. Revenue is expected to reach US$25,240.9m by 2028, growing at a 23.2% CAGR. Electronics leads (23.8%), followed by hobby/leisure (20.4%), fashion (18.9%), furniture/home goods (11.7%), groceries (9.4%), care products (8.2%) and DIY (7.6%).

Nonetheless, financial and technological barriers to developing and maintaining e-commerce websites compel many Bangladeshi business owners to select social commerce (s-commerce). S-commerce refers to the use of social media platforms for exchanging information among buyers, sellers and peers during the buying and selling of goods and services (Hashim & Carpenter, 2019). The principal objective of e-commerce is to enhance productivity. This is done through one-click transactions, virtual catalogs built upon specifications, and recommendations based on previous customers' purchasing patterns. Yet, buying is still a primary priority, s-commerce places more of an emphasis on social objectives, including networking, collaboration, and knowledge exchange (Hossain et al., 2024). Consumers frequently engage with e-commerce platforms through other consumers, but s-commerce involves online communities fostering social relationships to enhance customer involvement. S-commerce may be thought of as a subset of e-commerce (Abed, 2020), is different from e-commerce in terms of system operations, customer interactions, and organizational aims. A novel form of virtual trade, commonly referred to as s-commerce, has surfaced in the past few years due to the increasing popularity of social media and networking websites. S-commerce activities are highly engaging because of the social contact that occurs between consumers and involve interactions among all price chain stakeholders (Abed, 2020).

Small and medium-sized enterprises (SMEs) play a crucial role in a country’s economic growth (Rana, Barnard, Baabdullah, Rees, & Roderick, 2019). They comprise the largest business sector and have a significant impact on most global economies. Their flexibility, innovativeness and profit capacity explain this importance (Taylor, 2019). They play a key role in creating jobs locally and globally, supporting large manufacturers and broadening the base of production. Statista (2024) projects digital services revenue of $1.306 billion for 2024. This revenue will grow to $2,924 million by 2029 at a 17.5% CAGR. Dating services are expected to peak in 2025, with a 49% revenue increase. The growing popularity of digital transactions among the tech-savvy population is driving demand for online payment solutions in Bangladesh. Senarathna, Wilkin, Warren, Yeoh, & Salzman (2018) observe that SMEs tend to pay less attention to expertise to achieve optimal resource utilization. Zappala & Gray (2017) support this by stating that just one or two individuals are responsible for essential sectors of management activities. Moreover, SMEs face challenges, including economic instability, shortened product life cycles and market globalization (Puklavec, Oliveira, & Popovič, 2018).

To overcome these difficulties, SMEs must innovate in planning, productivity and human resources. They can drive emerging trends and address issues from globalization (Abed, 2020). One key trend is s-commerce among SMEs (Hossain et al., 2024). This trend presents numerous opportunities through demographic dynamics, geographic reach, shifting customer attitudes and advancements in technology. S-commerce has varied definitions. It blends computer science, psychology, sociology and marketing (Yaakub, Nor, & Jusoh, 2023). These fields give business practitioners many opportunities. In business, s-commerce is trade enabled by social media, combining offline and online settings (Wang & Zhang, 2012). It is a modern approach to trade, connecting all participants in the value chain. Livestreaming commerce also benefits SMEs by enabling them to instantly market their products and services (Hossain et al., 2024; Chen, Zhao, & Wang, 2020). Research shows livestreaming commerce is a revolutionary model. It enables active online exchanges between sellers and buyers, driving sales (Chen et al., 2020). Digitalization is crucial for every firm. Livestreaming commerce involves sellers and viewers showcasing products, providing demonstrations, offering discounts and answering customer questions (Hossain et al., 2024; Gupta et al., 2024; Chen et al., 2020). The growth of s-commerce and the impact of livestreaming require more attention from practitioners and academics (Hossain, Kalam, Nuruzzaman, & Kim, 2023).

Thus, the current study recognizes that s-commerce is likely to impact SMEs. It has significant economic value to both SME performance (Hossain et al., 2024; Chen et al., 2020) and national economic development. The study is based on the idea that SMEs can improve their financial performance by integrating social media into their operations. This can solve major problems they typically face. The study suggests that with the proper integration of technological factors (e.g. ICT, customer services, business processing), organizational factors (e.g. organizational culture, security and privacy, trust) and environmental factors (e.g. governmental support, business partners’ support), SMEs can succeed in adopting s-commerce and achieve their business objectives. In addition, Hsiao, Lee, & Chen (2015) argue that locus of control is a personality attribute that distinguishes people by their willingness to accept responsibility. Locus of control is recognized as a key element in the development of entrepreneurship, social capital and human capital, helping achieve business growth and sustain entrepreneurial intention (Hamzah & Othman, 2023). Thus, the current study includes locus of control as a moderator to gain a clearer understanding of s-commerce adoption in SMEs. Accordingly, the purpose of this study is to propose a competency model of s-commerce for SME performance based on the technology-organization-environment (TOE) framework. It also investigates the moderating effect of locus of control on s-commerce success. We examine s-commerce success through the TOE lens, following previous research on this framework in SMEs (Qalati, Yuan, Khan, & Anwar, 2021; Salah & Ayyash, 2024). Besides the research purpose, we outline three research questions:

RQ1.

How did TOE factors provide the groundwork for SMEs to adopt s-commerce?

RQ2.

Do TOE crucial aspects result in the success of s-commerce?

RQ3.

Does locus of control act as a moderator between TOE and s-commerce success, and if so, how?

^2.

Theoretical ground and hypothesis

^2.1

Theoretical underpinning

Since numerous researchers, particularly those focusing on modern firms, have put forth the theory of TOE (Qalati et al., 2021; Salah & Ayyash, 2024), the current study focuses on applying the TOE foundation for the adoption of s-commerce in SMEs. TOE was first proposed by Tornatzky, Fleischer, & Chakrabarti (1990), and it has since been supported by other experiments. According to Abed (2020) and Ng, Lit, & Cheung (2022), the TOE framework is an organizational-level paradigm that acknowledges the significant effects that technological, organizational and environmental factors have on decisions made by organizations. Purwandari, Otmen, & Kumaralalita (2019) argue that it is based not only on the development of the technology used but also takes organizational states into account from the perspectives of the internal and external environments. Abed (2020) notes that the TOE paradigm, which has substantial empirical support and a solid theoretical base, has been used to study how technological advancements are embraced. Qalati et al. (2021) suggest that technological factors should include relative advantage, cost-effectiveness, compatibility, interactivity and visibility, which have a strong influence on s-commerce adoption and SME performance. Tornatzky et al. (1990) argue that the environmental factor may also be described as the setting in which an organization establishes its operations. Several investigations have demonstrated the broad applicability and explanatory utility of the TOE model in various technological, industrial and national contexts (Qalati et al., 2021; Salah & Ayyash, 2024). They reported that the TOE framework can be extended by technological factors (e.g. relative advantage, compatibility, perceived risk, cost), organizational factors (technology readiness, strategic orientation), environmental factors (external pressure, technology vendor support, government support) and individual factors (top management support, CEO innovativeness, CEO experience). Hence, the current study proposes three main dimensions: technological, organizational and environmental, each with several subdimensions and conceptualizes a research model (see Figure 1).

Figure 1.
Conceptual research model

^2.2

Technological factors

Adam, Jizat, & Noor (2016) assert that over the past decade, organizations, particularly enterprises, have adopted information and communication technology (ICT) as a significant tool to enhance competitiveness within their organizations. ICT has revolutionized the way business is conducted, including the field of s-commerce. SMEs have been quick to adopt ICT as a means of improving their business operations and reaching a wider customer base through s-commerce, especially for attaining relative advantage, cost-effectiveness, compatibility, interactivity and visibility (Qalati et al., 2021). Abed (2020) reports that the perceived usefulness of technology has a strong influence on s-commerce adoption. Businesses across all sectors and industries have chosen to use ICTs to enhance their business value and improve operational efficiency, driven by intense market competition and a rapidly evolving business environment (Skafi, Yunis, & Zekri, 2020).

ICT applications play a crucial role in information dissemination and business-to-business networking, particularly in the integration of AI and customer tech-savviness (Salah & Ayyash, 2024). Gupta et al. (2024) note that SMEs’ perceived usefulness and reliability drive s-commerce adoption. ICT enhances SMEs’ innovation by providing fast access to external knowledge and stronger partner connections, leveraging their adaptability.

Liang, Ho, Li, & Turban (2014) define customer service quality as the degree to which a user evaluates the assistance and offerings of the service provider through websites or other platforms. Since social networking sites are increasingly used for business purposes in s-commerce, it is anticipated that social networking site design elements will have a significant impact on the social sharing and purchasing behavior of their members. The continued usage of s-commerce is thus positively impacted by this. Jeyaraj et al. (2023) reported that s-commerce features, social presence and familiarity are the primary factors influencing perceived trust, s-commerce adoption intention and actual adoption. Adam et al. (2016) state that social media, which initially made it easier for people to communicate with each other in virtual organizations, has now become an important part of communication, offering more opportunities for B2B and B2C transactions that benefit the country’s economy as a whole and support business development.

Business processing using technological factors in social commerce (s-commerce) refers to the various ways technology can be applied to s-commerce. This e-commerce model leverages social media platforms and networks to facilitate and optimize business operations. Some examples of technological factors that can be used to enhance business processing in s-commerce include e-commerce platforms, which are software applications that enable businesses to manage online sales, inventory and payments. In this regard, interactivity and visibility should be considered in technological constructs that have a notable impact on s-commerce adoption (Qalati et al., 2021). Demonstrating results is a key factor in the adoption of mobile commerce by SMEs. Social media management tools are software applications that enable businesses to manage their social media presence, such as scheduling posts, tracking engagement metrics and responding to messages. Accordingly, this study proposes the following hypothesis:

H1.

S-commerce success is positively influenced by ICT (H1a), customer services (H1b) and business processing (H1c).

^2.3

Organizational factors

According to Abed (2020), organizational factors such as top management support and organizational readiness have notable correlations with behavioral intentions to s-commerce adoption in the SME context. Perceived reputation has been considered in relation to perceived social value addition, which facilitates the behavioral intention of s-commerce adoption (Gupta et al., 2024). Hence, now is the ideal time to adopt s-commerce, using social media technologies. SMEs can gain a competitive advantage by using social media tools. From an organizational standpoint, SMEs have considerable potential to succeed in the current s-commerce market. SME culture must convey a positive message to adopt new social media technology, as its acquisition process is straightforward and allows for direct contact with consumers, requiring only minimal knowledge (Abed, 2020). However, innovation culture has been reported to harm e-commerce adoption by SMEs (Salah & Ayyash, 2024).

Due to insufficient policies and administration, this could raise significant customer concerns about privacy violations, primarily because when people use social media to purchase goods or services, they disclose their personal information (Wang & Herrando, 2019). Customers often want to conceal information, but when they have to disclose it to the seller, they must demand the highest security for their private data. If users believe their personal information is secure, they may be more likely to make purchases from SMEs via social media. By assuring stronger protection of their customers’ privacy from third parties, SMEs can prosper in the field. According to Ginosar & Ariel (2017), s-commerce or outside businesses may guarantee the security of the customer’s personal information.

Jeyaraj et al. (2023) noted that trust is a key determinant of intention to adopt s-commerce. More sales and contracts are possible for loyal SMEs than for ordinary SMEs. Most consumers endeavor to keep them secure, especially their data. By upholding customer confidence, SMEs can improve their reputation with clients. By liking, commenting and leaving favorable reviews on both their social media accounts and the business’s social media pages, customers interact with such reputable organizations. This research is crucial for understanding the various factors that affect consumers’ overall trust in social and e-commerce platforms. Accordingly, the following hypotheses are proposed:

H2.

S-commerce success is positively influenced by organizational culture (H2a), security and privacy (H2b) and trust (H2c).

^2.4

Environmental factors

S-commerce adoption has long been associated with environmental factors, such as consumer pressure and trading partner pressure (Salah & Ayyash, 2024; Abed, 2020), as well as competitive intensity, competitive pressure and the bandwagon effect (Qalati et al., 2021). Adoption is frequently hindered when the government imposes unique requirements that require multiple enterprises to possess strict control and testing equipment for industrial safety. According to Aljowaidi (2015), the government’s inability to provide an appropriate policy for SMEs is a contributing factor to the issue with social media adoption in SMEs. The government can achieve this by creating favorable conditions, such as tax breaks, infrastructure investment and regulatory oversight, to promote the use of technology by SMEs (Sugandini, Effendi, & Istanto, 2020).

Business partners’ support has been considered one of the key drivers of e-commerce adoption in SMEs, thereby enhancing marketing performance (Salah & Ayyash, 2024). Companies can benefit from growing rapidly, identifying new sources through diversification and innovating to offer products or services flexibly (Bustinza, Gomes, Vendrell-Herrero, & Baines, 2019). Gupta et al. (2024) argued that the legal and regulatory environment is a prime determinant of the perceived conditional value, which potentially impacts the behavioral intentions of SMEs regarding s-commerce adoption. Generally, companies keep their traditional products for sale during specific seasons when demand for those products is higher. In that case, a partner’s hand is extremely needed for SMEs. Accordingly, the following hypotheses are proposed:

H3.

S-commerce success is positively influenced by governmental support (H3a) and business partners’ support (H3b).

^2.5

Locus of control as moderator

A key personality characteristic that distinguishes people based on their readiness to accept responsibility for their actions is locus of control (Hsiao et al., 2015), considered as one of the prime factors of developing entrepreneurship, social capital and human (Hsiao et al., 2015) and entrepreneurial competency and thereby achieve business growth, quality of life and sustainable entrepreneurial intention (Hamzah & Othman, 2023). Two distinct perspectives on locus of control are presented, both of which are critical to s-commerce’s success (van Praag & van Witteloostuijn, 2004). Both kinds of locus of control significantly improve the overall dynamics and are necessary to ensure the success of s-commerce. Thus, both internal and external locus of control have a significant influence on entrepreneurial ambition.

According to Skudiene, Augutytė-Kvedaravičienė, Demeško, & Suchockis (2018), a moderating effect of locus of control is seen in the relationship between innovative work behavior and transformational leadership. They claimed that a stronger locus of control strengthens the connection between creative work practices and transformative leadership. They additionally claim that both internal and external loci of control have a direct effect on workers’ innovative performance. To enhance technological integration, improve organizational dynamics and navigate environmental effects, we believe that the internal and external locus of control work together in tandem, ultimately promoting the completion of s-commerce activities. Accordingly, the following hypotheses are proposed:

H4.

Locus of control moderates the association of s-commerce success with technological factors (H4a), organizational factors (H4b) and environmental factors (H4c).

^3.

Methodology

^3.1

Research methods

A structured instrument was used for the survey, and convenience snowball sampling was used to collect data, aiming to make it as easy as possible to reach the target population through participant referrals and direct contact. A pilot study involving 25 samples was conducted, and minor adjustments and alterations were made in response to the findings to enhance readability and consistency. Structural equation modeling was used following the two-step procedure described in Anderson & Gerbing (1988) guidelines, which used Amos-24 software and SPSS. Because it enables a real-time evaluation of both the measurement model and the structural model, the Amos-24 data analysis tool was specifically used to conduct the test (Anderson & Gerbing, 1988). This approach is very helpful in establishing the validity and reliability of the measurement model and in clarifying the theoretical relationships among the components of the structural model. By measuring a few model fit indices, its strength is further validated.

We adapted all measurement questions from the existing literature where all questions were measured using a seven-point Likert scale. The survey included four demographic features: age, gender, years of experience and monthly income. We collected 450 samples through various media, including Facebook business groups, online marketplaces, e-commerce platforms and other platforms, over the four weeks of December 2023. Following the cleaning and removal of the missing and unengaged samples, a final sample size of 414 was retained. There were mostly young people seated; 182 were between the ages of 20 and 25, which accounted for 44% of the total. Many of them had less than five years of experience, with 53.4% of the respondents having this level of experience and 24.9% having five to 10 years of experience (see Table 1).

Table 1.
Demographic characteristics

Factor	Category	Frequency (n = 414)	%
Age	Below 20 years	2	0.5
	20–25 years	182	44.0
	26–30 years	70	16.9
	31–35 years	44	10.6
	36–40 years	61	14.7
	More than 40 years	52	13.5
Gender	Male	237	57.2
	Female	177	42.8
Years of experience	Below five years	221	53.4
	5–10 years	103	24.9
	10–15 years	57	13.8
	15–20 years	14	3.4
	20–25 years	10	2.4
	More than 25 years	7	1.7
Income per month	Below 10,000 BDT	114	27.5
	10,000–20,000 BDT	101	24.4
	20,000–30,000 BDT	109	26.3
	30,000–40,000 BDT	45	10.9
	40,000–50,000 BDT	25	6.0
	More than 50,000 BDT	20	4.8

^3.2

Measurement model

The composite reliability (CR) ranged from 0.7 to 0.85. Scholars argued that the average variance extracted (AVE) should be at least 0.50 and the element loading should be larger than 0.60 to ensure convergent validity. All items had significant aspect loads of more than 0.60, as demonstrated in Table 2. Suitable convergent validity was demonstrated in this investigation by the AVEs, which varied from 0.50 to 0.60. The range of values for all the coefficients is 0.72–0.84, all of which fall inside their critical limits of 0.70. An AVE value of more than 0.5 is usually regarded as appropriate, while calculated values ranged from 0.50 to 0.60.

Table 2.
Reliability and validity statistics

Variable	Code	Mean	SD	Estimate	S.E.	t-value	p-value	Composite reliability (CR)	Average variance extracted (AVE)
Information and communication technology	ICT1	5.73	1.34	0.70				0.81	0.57
	ICT2	5.89	1.31	0.82	0.08	13.65	***
	ICT3	5.95	1.26	0.75	0.08	13.11	***
Customer services	CS2	5.60	1.35	0.71				0.73	0.50
	CS3	5.65	1.22	0.76	0.09	10.84	***
	CS4	5.71	1.25	0.59	0.09	9.76	***
Business processing	BP2	5.36	1.57	0.80				0.78	0.54
	BP3	5.52	1.54	0.65	0.07	12.14	***
	BP4	5.73	1.51	0.73	0.07	13.21	***
Organizational culture	OC1	5.62	1.32	0.73				0.82	0.53
	OC2	6.00	1.10	0.80	0.07	14.31	***
	OC3	5.93	1.15	0.71	0.07	13.04	***
	OC4	6.09	1.18	0.65	0.08	12.10	***
Security and privacy	SAP2	6.19	1.04	0.73				0.77	0.54
	SAP3	5.94	1.27	0.73	0.08	12.28	***
	SAP4	5.96	1.15	0.72	0.07	12.25	***
Governmental support	GS1	5.93	1.12	0.73				0.85	0.60
	GS2	5.91	1.06	0.80	0.08	15.02	***
	GS3	5.96	1.42	0.81	0.08	15.14	***
	GS4	5.63	1.56	0.73	0.09	13.83	***
Business partners’ support	BPS1	5.21	1.57	0.83				0.79	0.55
	BPS2	5.21	1.72	0.68	0.08	8.19	***
Trust	T1	4.82	1.78	0.77				0.82	0.54
	T2	4.30	2.01	0.64	0.06	12.61	***
	T3	5.23	1.68	0.83	0.08	16.20	***
	T4	5.81	1.47	0.67	0.09	13.21	***
Locus of control	LC1	5.27	1.64	0.84				0.75	0.50
	LC1	5.66	1.69	0.66	0.07	10.74	***
	LC3	5.32	1.68	0.58	0.07	9.89	***
S-commerce success	SCS1	5.95	1.19	0.69				0.82	0.60
	SCS2	5.75	1.34	0.96	0.11	12.55	***
	SCS4	5.88	1.17	0.58	0.07	10.55	***

• Note(s):***p < 0.001
• Source(s): Calculated results

In relation to discriminant validity, this study showed (see Table 3) that all the correlation values (ranging from 0.07 to 0.57) are within the standard limits, and the corresponding square roots of AVEs (ranging from 0.50 to 0.78) are higher than the correlation values, demonstrating that discriminant validity is unaffected. Every value in the variance inflation factors range of 1.10–1.49 is below the critical threshold of 5. Tolerance value is also within the critical value (ranging from 0.65 to 0.90). Furthermore, the Heterotrait-Monotrait criterion is fulfilled because none of the values (see Appendix 1) is higher than the criterion of 0.85. All together confirmed that our conceptual measurement methodology is ideal for achieving discriminant validity. Table 3 presents the standard measurement model, which fits the data properly (CMIN/DF = 3.01, RMSEA = 0.067, CFI = 0.92, TLI = 0.93, GFI = 0.90 and AGFI = 0.86), indicating a reasonable model fit.

Table 3.
Discriminant validity

Variable	Mean	SD	ICT	CS	BP	OC	SP	GS	BPS	T	LC	SCS	Tolerance	VIF
ICT	5.85	1.11	50										0.73	1.35
CS	5.65	1.02	0.39	0.70									0.80	1.24
BP	5.53	1.30	0.38	0.36	0.73								0.71	1.39
OC	5.91	0.95	0.26	0.26	0.46	0.73							0.75	1.32
SP	6.03	0.96	0.35	0.31	0.21	0.37	0.73						0.73	1.35
GS	4.88	1.47	0.12	0.21	−0.06	0.03	0.07	0.78					0.90	1.10
BPS	5.51	1.40	0.36	0.21	0.41	0.39	0.25	−0.07	0.74				0.79	1.25
T	5.85	1.04	0.43	0.40	0.46	0.37	0.57	0.09	0.25	0.73			0.65	1.52
LC	5.41	1.35	0.39	0.27	0.21	0.14	0.12	0.29	0.21	0.25	0.70		0.84	1.18
SCS	5.65	1.11	0.30	0.36	0.50	0.38	0.38	0.26	0.26	0.53	0.25	0.77	0.66	1.49

• Note(s): Italic diagonals are the square root of AVEs. Model fit indices CMIN/DF = 3.01; RMSEA = 0.067; CFI = 0.92; TLI = 0.93; GFI = 0.90 and AGFI = 0.86

^3.3

Hypothesis testing

The structural model demonstrated the highest prediction level of our model by accounting for 36% of the variance in s-commerce success. The overall model fit indices include CMIN/DF = 3.9, RMSEA = 0.079, CFI = 0.89, TLI = 0.90, GFI = 0.89 and AGFI = 0.83, all of which are acceptable.

Table 4 presents numerous pivotal factors that influence the achievement of s-commerce for SMEs within the TOE framework. Notably, ICT and business processing have a significant influence on s-commerce success, with t-values of 3.525 and 2.986, respectively; thus, H1a and H1c are accepted. These findings underscore the critical position of superior technological adoption and streamlined business procedures for SMEs engaging in s-commerce. Security and privacy, trust and governmental support also become influential factors, emphasizing the importance of these factors for s-commerce success. Maintaining data security, promoting consensus and benefiting from favorable government regulations are crucial, as highlighted in H2b, H2c and H3a. Conversely, customer services, organizational culture and business partners’ support do not exhibit significant effects, rejecting H1b, H2a and H3b. These nuanced findings offer valuable insights for practitioners and policymakers seeking design s-commerce techniques in the ever-evolving digital enterprise landscape, emphasizing the importance of targeted investments in technology, business processes, security features and government support for SMEs within the realm of s-commerce.

Table 4.
Hypothesis results

Paths	Estimate	S.E.	t-value	p -value	Decision
S-commerce success
ICT	0.181	0.050	3.525	***	H1a: accept
CS	0.053	0.052	1.062	n.s.	H1b: reject
BP	0.154	0.037	2.986	**	H1c: accept
OC	−0.078	0.046	−1.608	n.s.	H2a: reject
SP	0.225	0.056	4.167	***	H2b: accept
T	0.451	0.060	7.394	***	H2c: accept
GS	0.187	0.038	3.730	***	H3a: accept
BPS	−0.098	0.039	−1.415	n.s.	H3b: reject

• Note(s): Squared multiple correlations (R²): S-commerce success: 0.36. Model fit indices CMIN/DF = 3.9; RMSEA = 0.079; CFI = 0.89; TLI = 0.90; GFI = 0.89 and AGFI = 0.83. **p < 0.01; and ***p < 0.001; n.s. = not significant

^3.4

Moderation results

As per Bollen’s (1989) principles, the results shown in Figure 2 reveal that locus of control shows a noteworthy moderation effect in the links between business processing to s-commerce success (b = 0.099, t = 2.134), security and privacy to s-commerce success (b = 0.154, t = 3.44) and governmental support to s-commerce success (b = 0.110, t = 2.296) (see in Appendix 2). Unexpectedly, other paths do not exhibit significant moderation. Revealing that individuals’ locus of control over business processes, security and government support significantly affects s-commerce success, highlighting its role in SME performance.

Figure 2.
Pictorial view of moderation effects

^4.

Discussion and implication

^4.1

Key discussions on the findings

Our study shed light on numerous aspects, establishing a robust association between s-commerce success and the success of SMEs through the TOE model. ICT, business processing, security and privacy, trust and governmental support exhibited positive influence on s-commerce success, which corroborates (Gupta et al., 2024; Qalati et al., 2021; Wang & Herrando, 2019; Jeyaraj et al., 2023; Abed, 2020), who assert that the technology advantages, organizational preparedness and environmental potential of the TOE framework, all of which have a real impact on business performance, thus make it ideal for use in the context of SMEs. SMEs can enhance value and achieve their goals by leveraging online ICT and business systems, managing risks effectively, strengthening security and building trust to foster lasting relationships with both customers and employees. They can leverage government support to focus on adding client value, encouraging efficient and opportunistic use of resources. Nevertheless, the empirical data did not support H1b, H2a or H3b, indicating a need for a more sophisticated understanding of organizational culture, business partner support and customer service. This may be because most participants were sole proprietors or ran small teams, focusing less on organizational culture and managing the business themselves. They may operate mainly on their own funds, and small business owners may rely less on partner support, believing that handling all customer services themselves ensures satisfaction. This belief extended to staff, reinforcing that customer needs are met, thereby addressing the study’s conceptual RQ1 and RQ2.

Regarding RQ3, the findings indicate that an internal locus of control enhances the impact of business processes, security and government support on s-commerce success, partially supporting the findings of Skudiene et al. (2018). Firms’ innovative behavior increases with internal and external locus of control, providing SMEs with an advantage in s-commerce success through its moderating effect. SMEs with a higher internal locus of control are better equipped to leverage security and privacy, thereby gaining a competitive edge. While locus of control does not significantly affect s-commerce success in ICT, customer service, culture, trust or partner support, these factors remain vital for value creation, highlighting the complex relationships and the need to understand internal locus of control across dimensions.

^4.2

Theoretical implications

This study offers some significant implications for the theoretical domain. First, it successfully applied the TOE theory to s-commerce adoption by SMEs, accounting for 36% of the variance prediction, thereby offering new insights into the theoretical basis in s-commerce literature within the context of SMEs. In this country’s context, the application of the TOE theory made this study groundbreaking, offering useful insights to other countries with comparable circumstances. Second, our study highlights the importance of emerging technological advancements in the success of s-commerce, specifically emphasizing the benefits of using advanced generations and materials, particularly in terms of increasing business revenue and sales. It demonstrated how the successful incorporation of technological advancements improves the efficiency of SMEs’ operations, while lowering transaction costs and increasing customer satisfaction within the TOE framework. Overall, having a solid understanding of ICT will enable business owners to serve customers quickly and get advantageous positions in business processes, all of which will help them succeed in adopting s-commerce and improving firm performance. Third, it suggests that ensuring the security of sensitive personal and financial data promotes customer satisfaction, highlighting the critical role that organizational structure, culture, trust and capabilities play in predicting the success of s-commerce and firm performance. For SMEs to successfully integrate s-commerce into their operations, they need to assess their internal processes, policies and resources. This involves determining whether staff members are receptive to learning new technologies, whether data privacy and security protocols are in place, whether the necessary knowledge base is accessible and whether implementing social commerce aligns with company goals and plans. Adoption can also be aided by the presence of supportive leadership and an innovative culture. Perceived usefulness and trust have proved to be fundamental elements in interpersonal communication and trade interactions. Thus, we suggest that SMEs are far more likely to engage in s-commerce if they have a flexible organizational structure, a proactive approach toward innovation and a readiness to adapt to shifting market conditions.

Fourth, SMEs are under severe pressure to engage in s-commerce due to environmental factors, governmental support and business partners’ support to meet customer demand, as well as to survive in a competitive market. Our results demonstrate a positive response to government assistance, with most SMEs expressing satisfaction with the assistance they received. For the effective implementation of s-commerce, customer expectations and market competition should be taken into consideration. Adoption decisions can also be informed by knowledge about the competitive environment and industry peers’ s-commerce plans. Fifth, by adding and confirming locus of control as a moderator in TOE theory, we provide new perspectives. We contend that addressing security and privacy issues is more crucial in s-commerce than in any other traditional commercial method, which makes the locus of control a key driver. In the context of SMEs, it is essential to support them in accepting government assistance without reservation or fear of hardship, as this increases their confidence in running their business. Revealing a higher locus of control makes SME practitioners more realistic to the emerging techno-oriented environment, which could additionally add value to their firms.

^4.3

Managerial contributions

Regarding the managerial implications, this study offers SME managers invaluable insights by providing precise recommendations on various assumptions related to success factors in s-commerce. It is recommended that SME practitioners acknowledge the need to integrate with growing technological innovations; otherwise, they may fall behind others. Managers are advised to use these platforms, particularly s-commerce with its livestreaming capabilities, to stay current with consumer preferences. Without the high expenses of traditional marketing and e-commerce infrastructures, SMEs can now reach a wider range of consumers through e-commerce. This means that SMEs can reach both urban and rural consumers, increasing brand awareness without incurring significant capital investments. Through rigorous assessment of their organizational readiness, technological capabilities and external environment, practitioners of SMEs can develop a strategy plan for integrating social commerce into their operations. This strategic roadmap should include specific actions, due dates and performance metrics to ensure that social commerce initiatives align with the organization’s overall strategies.

Second, our research enables SMEs to enhance customer relationship management, facilitate real-time buyer–seller interactions and cultivate a loyal customer base. SMEs can market with data-backed accuracy and a higher return on investment by using integrated advertising tools and organic engagement through content and live broadcasts. Hence, SMEs can host training sessions to educate employees about s-commerce platforms and their benefits and they can also solicit feedback from suppliers and customers to enhance their social commerce strategies. Fostering a culture of collaboration and involvement helps enhance SMEs’ support and buy-in for the implementation of s-commerce, thereby enabling them to perform successfully. However, managers must exercise caution when dealing with technological elements, as they have the potential to mislead or incite customer mistrust. For example, to enhance the aesthetics of s-commerce performance, managers are advised to prioritize technical issues, such as record generation and data management. Similarly, focusing on social media channels for user-friendly online promotions and giveaways can increase interaction and engagement.

Third, managers must prioritize governmental support to maintain a competitive position in the market, as well as introduce new offerings, value co-creation and consumer satisfaction, as these are the foundations for both e-commerce and s-commerce. To create an environment that is favorable for SMEs involved in s-commerce, the government must intervene by enacting rules and laws. For example, resolving issues related to restricted access to popular online payment services, such as PayPal, in Bangladesh might make financial transfers for s-commerce SMEs easier and safer. By establishing an online presence on s-commerce platforms, SMEs can reduce their vulnerability to market saturation and economic downturns and also gain better access to global markets and establish connections with a customer base that is less reliant on local economies.

Finally, in dynamic economic situations, s-commerce fosters innovation and quick pivots by enabling SMEs to respond instantly to consumer needs and market trends through rapid testing and feedback. Hence, managers are advised to prioritize developing an internal and external locus of control among all employees of the firm, as this is crucial in enhancing their overall performance. A higher locus of control from SME owners, CEOs or employees is greatly desired to align with technology capabilities, organizational preparedness and environmental dynamics.

^5.

Conclusion

The goal of this study was to propose a competency model of s-commerce for SME performance, based on the TOE framework and to investigate the potential moderating influence of locus of control on the success of s-commerce. This study makes a substantial contribution to our understanding of the intricate factors influencing SMEs’ performance in s-commerce in Bangladesh, which are generalized to other similar nations. Our findings reaffirm the importance of ICT, security, privacy and regulation while clarifying their complex interrelations. The moderation analysis provides valuable insights into how the locus of control influences the relationship between TOE factors and s-commerce success.

We also acknowledge a few limitations of the study. First, although bias was minimized through careful survey design, reliance on online questionnaires and data from a single state limits generalizability, offering directions for future research. To develop a comprehensive understanding of s-commerce success in SMEs and to enhance robustness across nations, future studies should consider using diverse and comprehensive statistical series strategies across multiple countries to enhance the robustness and applicability of the outcomes. In addition, although this study examined SMEs across various industries, future research should target specific sectors and explore key digital marketing strategies for s-commerce success. Future researchers may consider including entrepreneurial experience, leadership styles and the level of digitalization in their studies.

Data availability statement

Data are available upon reasonable request.

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Appendix 1

Table A1.
HTMT analysis

Variable	ICT	CS	BP	OC	SP	GS	BPS	T	LC	SCS
ICT
CS	0.408
BP	0.382	0.382
OC	0.270	0.290	0.456
SP	0.369	0.322	0.289	0.382
GS	0.112	0.201	0.072	0.031	0.068
BPS	0.366	0.214	0.446	0.405	0.166	0.093
T	0.427	0.400	0.467	0.405	0.585	0.106	0.249
LC	0.383	0.277	0.256	0.164	0.101	0.265	0.227	0.259
SCS	0.381	0.346	0.410	0.212	0.470	0.204	0.127	0.612	0.216

• Note(s): There are no warnings for this HTMT analysis

Appendix 2

Table A2.
Moderation results

Paths	Estimate	S.E.	C.R.	P	Decision
ZSCS ← ZLC_ICT	0.031	0.035	0.654	n.s.	H4a: no
ZSCS ← ZLC_ZCS	−0.038	0.033	−0.797	n.s.	H4b: no
ZSCS ← ZLC_ZBP	0.099	0.044	2.134	**	H4c: yes
ZSCS ← ZLC_ZOC	−0.078	0.040	−1.623	n.s.	H4d: no
ZSCS ← ZLC_ZSP	0.154	0.051	3.440	***	H4e: yes
ZSCS ← ZLC_ZT	0.031	0.030	0.741	n.s.	H4f: no
ZSCS ← ZLC_ZGS	0.110	0.042	2.296	**	H4g: yes
ZSCS ← ZLC_ZBPS	0.013	0.041	0.274	n.s.	H4h: no

• Note(s): **p < 0.01 and ***p < 0.001, n.s. not significant

Edited by

• ASSOCIATE EDITOR:
  Luis Hernan Contreras Pinochet and Tatiane do Céu Silveira Santos.

Publication Dates

• Publication in this collection
  22 June 2026
• Date of issue
  2026

History

• Received
  16 Dec 2024
• Reviewed
  28 June 2025
• Reviewed
  02 Oct 2025
• Reviewed
  16 Oct 2025
• Reviewed
  20 Nov 2025
• Accepted
  16 Dec 2025