Structural Equation Modeling Methodology Research Articles

Role of influencer–follower congruence in influencing followers’ food choices and brand advocacy: mediating role of perceived trust

PurposeThis study attempts to encapsulate the idea of influencer marketing in the food sector and the vital role played by food influencers in shaping the dietary preferences, tastes and decisions of their social media followers and turning them into brand advocates.Design/methodology/approachAn online survey of 383 social media users, utilizing a self-administered questionnaire, was undertaken to validate the proposed research design. The partial least squares structural equation modeling (PLS-SEM) methodology was used to analyze the data and test the relationships between the constructs.FindingsThe results confirm the validity and reliability of the research model. The research revealed the positive influence of influencer–follower demographics and attitude congruence on followers’ food choices, which in turn leads to followers’ delight and significantly impacts their brand advocacy. It also depicts how followers’ perceived trust in an influencer mediates the relationship between their similarity with the influencers, their food choices and brand advocacy.Originality/valueThe study proposes a new theoretical framework and empirically tests the effectiveness of influencer marketing in influencing social media users’ food choice behavior and brand advocacy through the medium of followers’ congruence with social media influencers. The findings offer noteworthy theoretical and managerial implications for academicians as well as marketing practitioners.

Determinants of quality in airline service

Goal: This paper aims to identify the dimensions that impact the perception of the quality of Brazilian air services in the eyes of customers, using a questionnaire based on the SERVPERF model adapted for the service studied as a data collection instrument. Design/Methodology/Approach: The research used a quantitative approach, in which 810 questionnaires were analyzed using Structural Equation Modeling methodology. Results: The results showed that the relationship between quality perceived by clients and the dimensions of quality Tangibles and Empathy were those confirmed by Structural Equation Modeling in this research. The fact that the study is exploratory, and temporal indicates that in this period, Brazilian consumers attach more importance to the environment and appearance of aircraft, equipment, and employees of the companies and that their needs are met in a personalized way. Limitations of the investigation: Only Tangibles and Empathy dimensions were confirmed. Practical implications: With the feedback of the customer, including the constant need for an accuracy of the assumptions and hypotheses studied in this paper, an airline can identify what the real needs of its customer must be met and, in its strategic planning, identify the possible actions to be implemented, such as the priority of the investments, and, thus, to be able to increase the competitive advantage, offering the clients what they prioritize. Originality/Value: The information brought by this research can support the development of business strategies oriented in aspects related to tangible elements and empathy in the service to add value to the service perceived by the clients, contributing to the development of the activity and the sector.

Institutional pressure and responsible innovation: how big data analytics adoption drives manufacturing SMEs toward competitiveness

Purpose This study aims to examine the influence of regulatory framework (RF), market dynamism (MDY), competitive intensity (CIN) and environmental public concern (EPC) on responsible innovation (RI) in the manufacturing SMEs of a developing country. Furthermore, the study examines the influence of RI on sustainable competitive advantage (SCA). Moreover, big data adoption (BDA) is used as a moderator between RI and SCA. Design/methodology/approach The study’s hypotheses are evaluated using the structural equation modeling methodology. The study collected data from a sample of 487 owners/managers of manufacturing SMEs using simple random sampling technique. Findings The results explain that RF, MDY, CIN and EPC significantly determine RI. Moreover, RI significantly determines SCA. Besides, BDA significantly moderates between RI and SCA. Research limitations/implications For manufacturing SMEs to obtain SCA, RI is essential, and BDA is crucial to meet changing consumer demands for environmentally friendly products. With more environment-friendly initiatives, the natural environment will become more sustainable. Moreover, this research offers a comprehensive perspective to the public regarding the extent to which manufacturing enterprises are adopting RI and BDA. Originality/value The majority of earlier research on RI and BDA has been carried out in the context of large businesses. Institutional theory was used to look into the drivers of RI. Furthermore, BDA is used as moderating variable between RI and SCA.

Extending dramaturgical theory to evaluate revisit intention of international tourism: A scenario of COVID-19 tourism recovery

Since 2019, major travel destinations worldwide have issued travel-related restrictions against COVID-19. There is much research on tourism, but few studies have been conducted to explain the relevance of revisiting intention from the perspective of the epidemic or the dramaturgical theory. The purpose of the research is to explore the impact of customer experience on revisit intention during the period of COVID-19 slowdown by using dramaturgical theory. This study used a survey methodology, and the questionnaire was distributed on an online questionnaire platform. The URL of the questionnaire was published on social media (such as Facebook and LINE) to collect data from 389 samples of people who have foreign travel experience. The data was analyzed by employing partial least square structural equation model (PLS-SEM) methodology with the help of the statistical software “SmartPLS”. The research findings are as follows: 1) setting, audience, and performance are the three important elements of dramaturgical theory that impact the experience quality; 2) customer experience of tourists has a significant impact on the experience quality; 3) experience quality has a significant positive impact on the experience value and relationship quality; 4) experience value and relationship quality are important predictors of revisit intention. This study provides academic implications regarding the use of dramaturgical theory in relation to customer experience and relationship constructs in the context of tourism. Furthermore, it also provides some practical implications to tourism practitioners and managers, which would assist tourism industries in developing successful marketing strategies for the possible recovery of COVID-19.

Detecting causal relationships between work motivation and job performance: a meta-analytic review of cross-lagged studies

Given that competing hypotheses about the causal relationship between work motivation and job performance exist, the current research utilized meta-analytic structural equation modeling (MASEM) methodology to detect the causal relationships between work motivation and job performance. In particular, completing hypotheses were checked by applying longitudinal data that include 84 correlations (n = 4389) from 11 independent studies measuring both work motivation and job performance over two waves. We find that the effect of motivation (T1) on performance (T2), with performance (T1) controlled, was positive and significant (β = 0.143). However, the effect of performance (T1) on motivation (T2), with motivation (T1) controlled, was not significant. These findings remain stable and robust across different measures of job performance (task performance versus organizational citizenship behavior), different measures of work motivation (engagement versus other motivations), and different time lags (1–6 months versus 7–12 months), suggesting that work motivation is more likely to cause job performance than vice versa. Practical and theoretical contributions are discussed.

What factors contribute to the socioeconomic and socioenvironmental valorisation of heritage sites?

PurposeThe heritage and tourist attractiveness of Heritage Cities have aroused interest in establishing mechanisms to enhance their value based on the development of sustainability policies. The socioeconomic and socioenvironmental valuation of these heritage sites has become a necessary tool for decision-making.Design/methodology/approachFollowing the recommendations of International Council on Monuments and Sites – ICOMOS, this paper proposes a series of indicators and an exploratory model to define the factors that contribute to their valuation. Following the partial least squares structural equation modelling methodology, information was obtained from 363 intramural residents in the three Heritage Cities that currently have management plans in Spain.FindingsThe results show the importance of specifying indicators of sustainable mobility and socioeconomic and socioenvironmental sustainability for an adequate valorisation of heritage sites.Originality/valueTo this end, it is necessary to follow the guidelines of international bodies such as ICOMOS in relation to the management plans.

Towards a Holistic Understanding: Health Consciousness and Perceived Benefit in Consumer Choices of Hydroponic Products

Hydroponic products have emerged as a popular choice, particularly among urban populations opting for healthy food alternatives. This study aims to investigate the impact of health consciousness and perceived benefits on the purchase intention of hydroponic products. Additionally, it explores the mediating role of perceived benefits, concerning the Value-Based Consumer Decision Model. The study encompasses responses from 208 participants residing in Indonesia, obtained through snowball sampling techniques. The study utilizes structural equation modelling (SEM) methodology using SmartPLS 4 software. The findings elucidate the significant roles that health consciousness β 0.294 and perceived benefits β 0.393 play in shaping the purchase intention toward hydroponic products. Health consciousness as a crucial factor for perceived benefit β 0.483. This research delves deeper by developing a model to fill existing research gaps. It explores the mediating role of perceived benefit in influencing the relationship between health consciousness on purchase intention β 0.190, the model reveals that perceived benefit successfully mediates the influence of health consciousness on purchase intention. This research is novel in its application of the value-based consumer decision model to the consumer behavior associated with hydroponic products. It offers important implications for business practitioners in the hydroponic product sector, providing invaluable insights into the shifting market dynamics driven by an increasingly health-conscious and benefit-oriented consumer base.

Exploratory analysis of zero waste theory to examine consumer perceptions of sustainability: A covariance-based structural equation modeling (CB-SEM)

IntroductionThe analysis of corporate and consumer sustainability practices is currently the focus of several scientific disciplines due to their environmental impact and diversity. ObjectiveThis research aims to create a hierarchy of consumer perceptions of zero waste thinking that can guide government decisions regarding university communities' sustainability efforts. To achieve the objectives of this study, Hungarian university citizens (students, faculty, staff) as potential zero waste consumers in Győr were involved in a purposive sampling approach. MethodsThis study adopted the Covariance-Based Structural Equation Modeling (CB-SEM) methodology to prove the hypotheses related to the 7Rs regarding Zero Waste perceptions of university citizens. The rethink element of the hierarchy was defined as the default condition for the 7 R application and therefore remained at the top of the hierarchy as an endogenous variable. ResultsThe study concluded that it is possible to adapt a business 7 R framework for consumer use, but only 5Rs can be applied. The analysis was conducted at a 90% confidence level, under which condition the independent variables together explain 87% of the variance of the rethink factor. The results show that the four constructs, namely rot (β =0.12, ρ<0.1), reduce (β =0.21, ρ<0.1), recycle (β =0.26, ρ<0.05), and reuse (β =0.43, ρ<0.05) significantly affect rethinking. Based on these regression weights, a hierarchy of importance can be established. In line with the original 7 R business concept, rethink is at the top of the hierarchy, followed by the other elements. ConclusionsThe results suggest that the zero waste attitudes of university citizens are currently limited to the 5Rs, which should require government leadership to strengthen these factors or a more consistent presence and support for the 2Rs that are missing from the established model. Governments can use the results of this research in their sustainability-related decisions.

Knowledge sharing leads to engagement during Covid-19 for online gamers

Online games have emerged as a breath of fresh air in the lives of the current digital generation amidst the backdrop of COVID-19 and subsequent global lockdowns. Within Internet communities, online gamers actively engage in knowledge sharing, exchanging insights and updates on their experiences. This study introduces a model designed for Massive Multiplayer Online Gamers of Travian, focusing on intrinsic factors such as perceived usefulness, perceived ease of use, and the flow state, supported by the Technology Acceptance Model. Amidst the COVID-19 pandemic, with lockdowns and quarantine as moderators, this study uses partial least squares structural equation modeling (PLS-SEM) methodology, encompassing 496 gamers, to elucidate the impact of technology acceptance and flow theory on intrinsic motivational factors that drive online gamers' knowledge-sharing activities, underpinning the social protection theory. This pioneering research explores the implications of COVID-19 restrictions on gamers' behavioral patterns, contributing significantly to the existing literature by providing a deeper psychological understanding of the less-explored realm of diverse online gamers' activities during the pandemic.

Will Artificial Intelligence be a Performance Booster to Agritech Start-Up?: Empirical Evidence from Emerging Economy

Indian agriculture is in the period of transition from traditional to modern agriculture. The role of various technologies in solving contemporary global issues is inevitable in any business sector, likewise in agriculture. This research work attempts to understand the impact of one such technology, Artificial Intelligence (AI) on the agricultural value chain. Quantitative research methodology is followed in this research work and data is obtained from the agri companies that use AI for their operations and decision-making. A conceptual model is also developed for this purpose. Structural Equation Modeling (SEM) methodology is adopted to understand the relationship between barriers, benefits, and the future of AI and the performance of the agri value chain. Hypotheses are developed for this purpose and tested based on the data collected from agritech companies. The result obtained proves that the benefits of AI and the future of AI have a positive impact on the value chain performance which in turn have a positive influence on organizational performance. However, it is found that barriers to AI adoption do not have much influence on adopting it and on the value chain performance of agritech companies. One of the major contributions of this research work is that it would be useful to the practitioners/Government in framing policies on implementing technologies in the agricultural sector.

Values and economic performance across European welfare state regimes: Direct and indirect effects through social capital, human capital and managerial skills.

The values that people hold are linked to their economic performance. These links can be either direct or indirect, operating through moderating variables such as social network participation, interpersonal trust, trust in institutions, human capital, managerial skills and hours worked. In this paper these effects are studied using structural equation modelling (SEM) methodology applied to European Social Survey data from 28 European countries in 2018. Schwartz classification of values is used, distinguishing between Self-Enhancement (Power, Achievement), Openness to Change (Self-Direction), Conservation (Tradition, Security, Conformity) and Self-Transcendence (Universalism, Benevolence) values. It is found that Power has the strongest positive direct effect on economic performance, further strengthened by a positive indirect structural effect through hours worked. Self-Direction is indirectly positively linked to economic performance through higher managerial skills and hours worked. Tradition has a strong negative direct effect on economic performance. Security is indirectly negatively linked with economic performance, owing to its negative effects on interpersonal trust, management skills and hours worked. Some of the identified effects are context-dependent and vary across European welfare state regimes. For example, Power is statistically significantly linked to economic performance only in the liberal and conservative regime. Values promoted by respective welfare state regimes are not necessarily associated with higher incomes within those regimes, e.g., Tradition and Security values promoted in the conservative and Mediterranean regime are associated with lower incomes. These findings may lead to a range of policy implications, particularly in relation to the policies on immigration, demographics, the labor market, and work-life balance. Unfortunately, due to the cross-sectional character of the dataset, causal relations among the variables of interest could not be identified.

User acceptance of social network-backed cryptocurrency: a unified theory of acceptance and use of technology (UTAUT)-based analysis

Turbulent market conditions, well-publicized advantages, and potential individual, social, and environmental risks make blockchain-based cryptocurrencies a popular focus of the public and scientific communities. This paper contributes to the literature on the future of crypto markets by analyzing a promising cryptocurrency innovation from a customer-centric point of view; it explores the factors influencing user acceptance of a hypothetical social network-backed cryptocurrency in Central Europe. The research model adapts an internationally comparative framework and extends the well-established unified theory of acceptance and use of the technology model with the concept of perceived risk and trust. We explore user attitudes with a survey on a large Hungarian sample and analyze the database with consistent partial least square structural equation modeling methodology. The results show that users would be primarily influenced by the expected usefulness of the new technology assuming it is easy to use. Furthermore, our analysis also highlights that while social influence does not seem to sway user opinions, consumers are susceptible to technological risks, and trust is an important determinant of their openness toward innovations in financial services. We contribute to the cryptocurrency literature with a future-centric technological focus and provide new evidence from an under-researched geographic region. The results also have practical implications for business decision-makers and policymakers.

Green Training, Green Recruitment, and Green Transformational Leadership on Employee Performance in Retail Store

Purpose: This study aims to investigate how green training, green recruitment, and green transformational leadership affect employee performance at self-service retail in Yogyakarta, Indonesia.&#x0D; Study design: The study was carried out with a quantitative methodology, application of a quantitative research strategy, specifically by giving respondents questionnaires. There are 214.000 responders in this research population, while with the slovin formulation a sample of 178 respondents was obtained. The Cluster Sampling technique is applied in Probability Sampling to take the sample. Utilizing the Variance Based Structural Equation Modeling (SEM) methodology, the SmartPLS program version 4.0 was tested for validity and reliability using an analytical tool.&#x0D; Findings: The research results show that Green Training has a significant positive effect on Employee Performance, Green Recruitment has a significant positive effect on Employee Performance and Green Transformational Leadership has no significant effect on Employee Performance.&#x0D; Originality/value: This research contributes to research on retail companies where research is very rarely conducted, especially on green management research, from an employee perspective.

The Intention to Use of a New Mobile Apps: A Case from Customers of an Indonesian Electrity Company

Mobile apps are now an integral part of our daily life which brought quite significant changes in consumer behavior. Therefore, the development of electronic service quality becomes a crucial factor to consider in determining whether digital transformation affects customer satisfaction. PT PLN (Persero), the Indonesian Electricity Company launched their new mobile apps in 2022 with the objective to provide better customer engagement and service. New PLN Mobile is an application used by PT PLN (Persero) to facilitate customers in enjoying every service provided by the company. This study integrates constructs from the mobile-technology acceptance model (M-TAM) and unified theory of acceptance and use of technology model (UTAUT) into a new theoretical model and tests them to a one of rural regions in Indonesia. The study was conducted by using a structured questionnaire to collect data from 566 respondens of customers of PT PLN (Persero) PLN ULP Jeneponto. The research model was assessed using the partial least squares structural equation model (PLS-SEM) methodology, facilitated by the Smart PLS software to provide insights into the factors that determine the acceptance of technology, which can explain user behavior. The analysis results are expected to identify the factors of customer readiness in adopting the New PLN Mobile electronic service in Jeneponto Regency. The results revealed significant relationships for all of the hypotheses. Mobile Usefulness to Intention to Use (H1), Mobile Ease of Use to Intention to Use (H2), Social Influence to Intention to Use (H3), Facilitating Condition to Intention to Use (H4) and Intention to Use to Actual Use (H5) showed t-stat values respectively, surpassing the standard test value. In the results, it can also be observed that the most significant factor influencing Intention to Use is Facilitating Condition.

From storefront to screen: an in-depth analysis of the dynamics of online for offline retailing

Within the rapidly changing online sphere, the significance of online for offline (O4O) commerce platforms in directing consumer choices is evident. The purpose of this research is to examine the factors that influence consumer shopping motives within the context of O4O commerce. The value of this study lies in its enhancement of our understanding of how various factors within the O4O model impact consumer decision-making processes. This offers significant insights for businesses and marketers, enabling them to strategize more effectively for customer engagement and retention. The study analyzed a dataset of 272 consumers who were familiar with O4O platforms, utilizing the Partial Least Squares Structural Equation Modeling (PLS-SEM) methodology, specifically conducted through the SmartPLS software program. The results revealed that effort expectancy has a connection with continuance intention but remains unrelated to shopping intention. In contrast, performance expectancy was influential in both continuance and shopping intentions. Social influence showed a strong relationship with continuance intention, yet lacked significance with shopping intention. Facilitating conditions primarily directed continuance intention, without influencing shopping intention. The study also validated the relationship between continuance intention and shopping intention, highlighting innovativeness as a key moderator in the bond between social influence and continuance intention. These insights offer valuable perspectives for industry professionals, elucidating factors that drive consumer interactions on O4O commerce platforms.

The Influence of Social Media Marketing Activities on Brand Loyalty in Mobile Phone Products

Marketing activities through social media have become a common practice in the 21st-century business world. This has facilitated direct interaction between companies and consumers, engaging them in direct communication. This study aims to systematically and comprehensively examine the impact generated by social media marketing activities (SMMA) on the creation of brand awareness, brand image, and perceived quality. The research will measure the impact on brand equity resulting from the utilization of SMMA, specifically focusing on its influence on brand loyalty concerning mobile phone products within Indonesian society. The research will employ data collection through surveys and Structural Equation Modeling (SEM) methodology. The findings indicate that Social Media Marketing Activities (SMMA) have a positive and significant impact on brand awareness, brand image, and perceived quality. Furthermore, brand awareness, brand image, and perceived quality are proven to positively and significantly influence brand loyalty. Brand equity, represented by brand awareness, brand image, and perceived quality, has shown the ability to mediate the relationship between SMMA and brand loyalty. Further research could delve into the impact of SMMA on customer equity and expand the study by incorporating additional variables related to brand loyalty. Companies may benefit from investing in marketing efforts utilizing social media platforms as effective marketing tools.

Navigating the Future: Exploring AI Adoption in Chinese Higher Education Through the Lens of Diffusion Theory

Aim/Purpose: This paper aims to investigate and understand the intentions of management undergraduate students in Hangzhou, China, regarding the adoption of Artificial Intelligence (AI) technologies in their education. It addresses the need to explore the factors influencing AI adoption in the educational context and contribute to the ongoing discourse on technology integration in higher education. Background: The paper addresses the problem by conducting a comprehensive investigation into the perceptions of management undergraduate students in Hangzhou, China, regarding the adoption of AI in education. The study explores various factors, including Perceived Relative Advantage and Trialability, to shed light on the nuanced dynamics influencing AI technology adoption in the context of higher education. Methodology: The study employs a quantitative research approach, utilizing the Confirmatory Tetrad Analysis (CTA) and Partial Least Squares Structural Equation Modeling (PLS-SEM) methodologies. The research sample consists of management undergraduate students in Hangzhou, China, and the methods include data screening, principal component analysis, confirmatory tetrad analysis, and evaluation of the measurement and structural models. We used a random sampling method to distribute 420 online, self-administered questionnaires among management students aged 18 to 21 at universities in Hangzhou. Contribution: This paper explores how management students in Hangzhou, China, perceive the adoption of AI in education. It identifies factors that influence AI adoption intention. Furthermore, the study emphasizes the complex nature of technology adoption in the changing educational technology landscape. It offers a thorough comprehension of this process while challenging and expanding the existing literature by revealing the insignificant impacts of certain factors. This highlights the need for an approach to AI integration in education that is context-specific and culturally sensitive. Findings: The study highlights students’ positive attitudes toward integrating AI in educational settings. Perceived relative advantage and trialability were found to impact AI adoption intention significantly. AI adoption is influenced by social and cultural contexts rather than factors like compatibility, complexity, and observability. Peer influence, instructor guidance, and the university environment were identified as pivotal in shaping students’ attitudes toward AI technologies. Recommendations for Practitioners: To promote the use of AI among management students in Hangzhou, practitioners should highlight the benefits and the ease of testing these technologies. It is essential to create communication strategies tailored to the student’s needs, consider cultural differences, and utilize the influence of peers and instructors. Establishing a supportive environment within the university that encourages innovation through policies and regulations is vital. Additionally, it is recommended that students’ attitudes towards AI be monitored constantly, and strategies adjusted accordingly to keep up with the changing technological landscape. Recommendation for Researchers: Researchers should conduct cross-disciplinary and cross-cultural studies with qualitative and longitudinal research designs to understand factors affecting AI adoption in education. It is essential to investigate compatibility, complexity, observability, individual attitudes, prior experience, and the evolving role of peers and instructors. Impact on Society: The study’s insights into the positive attitudes of management students in Hangzhou, China, toward AI adoption in education have broader societal implications. It reflects a readiness for transformative educational experiences in a region known for technological advancements. However, the study also underscores the importance of cautious integration, considering associated risks like data privacy and biases to ensure equitable benefits and uphold educational values. Future Research: Future research should delve into AI adoption in various academic disciplines and regions, employing longitudinal designs and qualitative methods to understand cultural influences and the roles of peers and instructors. Investigating moderating factors influencing specific factors’ relationship with AI adoption intention is essential for a comprehensive understanding.

Technology Acceptance of Wearable Collaborative Augmented Reality for Mathematics Education in A Junior High School

The Wearable Collaborative Augmented Reality (WcAR) represents a state-of-the-art advancement in computer technology, exhibiting diverse applications across various domains. Despite the increasing recognition of WcAR as an emerging educational technology, there exists a compelling need for further research, particularly in the context of mathematics education at the junior high school level. This research focuses on examining learners' acceptance of technology concerning Wearable Collaborative Augmented Reality (WcAR). The study utilizes data collected through questionnaires distributed after learners have interacted with the Hololens 2 device. To rigorously evaluate the proposed relationships, this investigation employs the methodology of Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings of the study reveal a statistically significant positive correlation between three extension structures—Interaction, Imagination, and Innovation—and the constructs of the Technology Acceptance Model (TAM), namely Perceived Usefulness and Perceived Ease of Use. Consequently, these results offer empirical support for the assertion that Wearable Collaborative Augmented Reality (WcAR) technology has the potential to be an effective tool for enhancing junior high school mathematics instruction. This empirical validation establishes a crucial theoretical foundation for subsequent empirical research endeavors in this domain. Furthermore, the study also discovers that WcAR technology can cultivate students' spatial understanding, providing valuable practical insights for the field of mathematics education.

LOAN CHARACTERISTICS &amp; LOAN CREDIT TERMS: DOES IT MATTER IN A MICROFINANCE CONTRACT?

This study examined the relationship between loan characteristics and loan credit conditions on loan repayment issues in order to assist Microfinance Institutions (MFIs) in Pakistan in improving their loan payback performance. The study also examines the link between loan credit terms and problems with loan repayment as well as the mediating function of client-business performance in the relationship between loan characteristics and loan repayment concerns. A measurement model and a structural model were both used in this investigation, which used a two-stage structural equation modelling methodology. The measurement model, also known as the outer model, was employed to evaluate the reliability and validity of the data collection technology. PLS-SEM bootstrapping was performed to test the hypothesis using the structural model (inner model). The results are consistent with the assumption that loan terms and conditions have a positive impact on microenterprise loan repayment concerns. The findings of this study also lend credence to the idea that client-business performance functions as a mediator in the relationships between loan characteristics and problems with loan repayment as well as between loan credit terms and problems with loan repayment. There hasn't been much research done in Pakistan to date on how loan characteristics and loan credit terms directly affect the challenges microenterprises face in repaying loans. The business performance of microenterprises is also investigated in relation to loan features, loan credit terms, and loan repayment issues.

Relating the strategic role of technology orientation in organizational TQM performance

The importance of incorporating cutting-edge technological strategies to support business ecosystem development is growing across industries. By examining the relationship between organisational Total Quality Management (TQM) performance and the indicators of technology orientation, this study aims to fill the knowledge gap caused by insufficient empirical research on the characteristics of technology orientation. This study evaluates a unique conceptual framework using survey data from 254 IT manufacturing companies in India, utilising a two-staged structural equation modelling and artificial neural network methodology. The study developed hypotheses on TQM organisational performance through the literature on technology orientation to determine the correlations between these indicators. The findings highlight how enterprises that commit to adopting new technologies can enhance technological innovation to become more resourceful and creative and increase organisational TQM performance. The sensitivity analysis results showed that technology adoption significantly impacts organisational TQM performance. The novelty of this study contributes to the literature on organisation TQM performance by providing a deeper understanding of relevant technology orientation indicators and how organisations should use them to achieve superior performance. The results show that technology acceptance strategy, capability, infrastructure, innovation, and adoption benefit organisational TQM performance.