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This paper aims to review and highlight the gaps in the research streams of the technological acceptance model (TAM) associated with e-banking services. The introduction of TAM as a decision-making process from individual and organizational perspectives is the core purpose of this paper.

This study is based on concept-centric reviews and synthesizing of previous research. Data are extracted from a systematic literature review published from 1975 to 2021 under the preferred reporting items for systematic review and meta-analyses statement.

This review explored that theory of reasoned action and theory of planned behavior are the basic theories proceeding to TAM evolution. TAM has been extended to its three versions, which are designed and modified for different contexts and cultures. Previously, the risk-return approach, theory of trust and perceived value were the major constructs or modifications in TAM. Now, TAM has been designed for measuring customers’ perception of any technological advancement.

This review is limited to major additive constructs in modified TAM concerning e-banking services, which can be expanded to different cultures and contexts. This study sketched TAM as a decision-making model associated with the factors influencing any technological advancement. So, the proposed conceptual framework is applicable for the behavioral analysis of technological adoption from individual and organizational perspectives in any field.

This review designed a bi-dimensional conceptual model of TAM as a decision-making process for e-services that has not been identified yet in any study from organizations’ and customers’ perspectives.

This study aims to explore the factors that influence young green actual consumption behavior (GACB) by examining the relational and technological aspects that are dependent on technology and youth green buying intention (GBI). Additionally, this study endeavors to examine the moderating effect of adolescent green organizational citizenship behavior (OCB) on the association between young consumer GBI and young GACB.

The data for this study was collected from a sample of 282 university students located in the southern region of China. A time lag approach was used in this study, with data being gathered during two separate intervals spaced apart by duration of two months.

The findings of this study demonstrate that both technological and relational factors play a significant role in predicting young consumer GBI, which in turn predicts young GACB. Additionally, the results indicate that GBI is a crucial facilitator in the investigation. Furthermore, the results reveal that young green OCB serves as a significant moderator, enhancing the association between young consumer GBI and young consumer GACB.

The present study provides a novel perspective on the examination of how technology and relational factors impact young consumers, offering a deeper understanding of their intentions and actual consumption behavior. The findings of this study offer both theoretical and practical implications for academics, policymakers, senior managers and practitioners, providing valuable insights into the field.

This study explores how app store awards shape the behavior of leading digital entrepreneurs, focusing on their engagement in technological innovation through feedback and re-signaling mechanisms. It aims to reveal the nudging effect of award signals on entrepreneurial behavior.

In this study, data from 349 leading mobile app entrepreneurs in the UK Google Play Store were collected over an extended period from various sources. Functionality novelty and explorative behavior were assessed by analyzing app release date and permission technologies in comparison to both their own prior apps and those of their closest competitors. Hypothesized relationships were tested using accelerated failure time parametric models.

This study extends the literature on signaling by showing that (1) the top developer award signal served to nudge entrepreneurs to improve the functionality novelty of their apps and those who succeeded were less likely to switch to another product category, (2) the award signal created a window of opportunity for non-award entrepreneurs to respond and those who released new apps around the midpoint of a normal app development cycle significantly improved the likelihood of winning the award in a subsequent round of award-giving, and (3) the effect of functionality novelty on winning the award was more pronounced when non-award entrepreneurs pursued more explorative than exploitative behavior in app development.

The results offer novel insights into an understudied area, specifically the influence of online award signals on nudging entrepreneurs to pursue technological innovation. The research also highlights the crucial role played by the app store as an intermediary signaler.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

Knowledge search is considered a broad concept and semi-intentional behavior. The path and boundary conditions through which search strategies affect intra-organizational knowledge creation remain elusive. Drawing on recombinant search theory and knowledge-based view, the authors seek to identify knowledge complexity as an important intermediate variable between knowledge search and innovation performance, such as research and development (R&D) output and R&D output quality. A second goal of this study is to examine the moderating roles of government support and technological turbulence.

The authors employed a longitudinal panel of 609 global pharmaceutical firms and obtained the firms' patent records from 1980 to 2015 for the analysis. The authors used generalized estimating equations (GEE) to evaluate the models and tested the consistency via panel fixed-effects estimations.

The authors' findings show that organizational routine-guided search has a negative effect on knowledge complexity, while routine-changing search exerts a positive impact on knowledge complexity. Governmental support and technological turbulence moderate these relationships. Notably, knowledge complexity has an inverted U-shaped relationship with innovation performance.

The authors' research context, the pharmaceutical industry, may constrain the generalizability of our findings. In addition, potential types of routine-guided and routine-changing search behaviors were not considered.

Despite these limitations, this study offers important implications. First, knowledge complexity transmits the effects of knowledge search on innovation performance. Practitioners should balance routine-guided and routine-changing search processes to build and manage complex knowledge. Second, a moderate level of knowledge complexity is the key to good R&D output and R&D output quality.

The study identifies knowledge complexity as one important intermediate variable between knowledge search behaviors and intra-organizational knowledge creation.

The paper aims to elucidate effective strategies for promoting the adoption of green technology innovation within the private sector, thereby enhancing the value of public–private partnership (PPP) projects during the operational phase.

Utilizing prospect theory, the paper considers the government and the public as external driving forces. It establishes a tripartite evolutionary game model composed of government regulators, the private sector and the public. The paper uses numerical simulations to explore the evolutionary stable equilibrium strategies and the determinants influencing each stakeholder.

The paper demonstrates that government intervention and public participation substantially promote green technology innovation within the private sector. Major influencing factors encompass the intensity of pollution taxation, governmental information disclosure and public attention. However, an optimal threshold exists for environmental publicity and innovation subsidies, as excessive levels might inhibit technological innovation. Furthermore, within government intervention strategies, compensating the public for their participation costs is essential to circumvent the public's “free-rider” tendencies and encourage active public collaboration in PPP project innovation.

By constructing a tripartite evolutionary game model, the paper comprehensively examines the roles of government intervention and public participation in promoting green technology innovation within the private sector, offering fresh perspectives and strategies for the operational phase of PPP projects.

Virtual grocery shopping (VGS), or online grocery shopping, traditionally has seen slow adoption in Canada; however, the COVID-19 pandemic has forced consumers to seek safer ways to shop. Retailers have invested in building new infrastructure to meet the current consumer demands for VGS. However, the main driver for VGS behaviour has not been yet clearly identified. Additionally, it is also not unknown whether the shopping modalities will continue VGS after the pandemic. This study provides insights into consumer intentions to use VGS by extending the model of goal-directed behaviour (MGB) to incorporate consumer technological readiness.

The study collected 935 valid survey responses from an online survey panel of Canadian consumers. A two-step approach was applied to analyse the data, comprising confirmatory factor analysis (CFA) and structural equation modelling (SEM). The data quality and model fit were tested before testing the proposed relationships among the constructs: attitude, subjective norm, perceived behavioural control, positive and negative anticipated emotions, as well as technological readiness, desire and behaviour intentions. The mediation role of desire between frequency of past online grocery shopping behaviours and the future behavioural intention was also tested using SPSS PROCESS.

The study results showed that attitudes, subjective norms, perceived behavioural control, positive and negative emotions, technological readiness and frequency of past VGS have a major impact on consumers' desire to embrace VGS in the future. Consumer desire also played a significant mediating role between frequency of past VGS behaviours and future shopping intention online. In addition, the frequency of past VGS showed an even stronger impact on behavioural intention among female consumers than among male consumers.

The findings of this study provide an original insight into the social, cultural and psychological factors that impact consumers' use of VGS, particularly the impacts of gender.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

The world of work is changing rapidly as a result of technology, with more workers being impacted by automation, the gig economy and temporary work contracts. This study focusses on how employees perceive their disruption knowledge and how this perception impacts their career planning, career satisfaction and training behaviors.

The authors use data from 1,516 employees across a broad range of industries and professions from the United States (n = 505), New Zealand (n = 505) and Australia (n = 506).

The authors find that an employee's knowledge and research into automation positively influence how employees plan their careers, their career satisfaction and their training behaviors. While career planning is positively related to career satisfaction and training behavior, career satisfaction is negatively related to training behaviors. The authors test mediation effects and find consistently significant indirect effects, and these findings are all largely replicated across the three countries.

This study highlights the importance of understanding the processes that employees go through when thinking about disruption knowledge, their careers and the impact on their training behaviors.

Long sales periods (i.e. Christmas time, Black Friday, etc.) and the risk of contagion while shopping (i.e. during pandemics like COVID-19) showed the extent to which crowded shopping environments have negative effects on consumers’ behavior. Hence, using terror management theory (TMT) and stimulus–organism–response (S–O–R) approach, the authors aims to develop a new model to investigate the effect of crowd-checking technology on shopping anxiety, the perceived value of shopping experience and willingness to pay.

Using a cross-sectional research design and with a help of an independent research company, the authors collected 1,000 valid responses from individuals residing in the UK.

Results showed that crowd-checking technology cues reduce shopping anxiety, improve value perceptions and increase willingness to pay. In addition, the efficacy of technology in reducing shopping anxiety is moderated by customers’ shopping orientation.

To the best of the authors’ knowledge, this research is the first one investigating crowd monitoring systems used at the initial stage of consumers’ journey to show the number of consumers in-store in real-time. It contributes to the literature on technology applications in retailing by providing evidence that technology cues reduce shopping anxiety, which in turn enhances customer-perceived value from the shopping experience and increases the willingness to pay in stores with embedded crowd-checker technology. The study also extends the application of TMT in a new context.

Los largos periodos de rebajas (ej. Navidades, Black Friday, etc.) y el riesgo de contagio durante las compras (ej. durante pandemias como la COVID-19) mostraron hasta qué punto los entornos de compras abarrotados tienen efectos negativos en el comportamiento de los consumidores. Utilizando la Teoría de la Gestión del Terror (TMT) y el enfoque Estímulo-Organismo-Respuesta (S-O-R), desarrollamos un nuevo modelo para investigar el efecto de la tecnología de control de multitudes sobre la ansiedad en las compras, el valor percibido de la experiencia de compra y la disposición a pagar.

Utilizando un diseño de investigación transversal y con la ayuda de una empresa de investigación independiente, recogimos 1.000 respuestas válidas de personas residentes en el Reino Unido.

Los resultados mostraron que las señales de la tecnología de comprobación de multitudes reducen la ansiedad en las compras, mejoran la percepción del valor y aumentan la disposición a pagar. Además, la eficacia de la tecnología en la reducción de la ansiedad de compra está moderada por la orientación de compra de los clientes.

Esta investigación es la primera que estudia los sistemas de seguimiento de multitudes utilizados en la fase inicial del viaje de los consumidores para mostrar el número de consumidores en la tienda en tiempo real. Contribuye a la literatura sobre aplicaciones tecnológicas en el comercio minorista aportando pruebas de que las señales tecnológicas reducen la ansiedad de compra, lo que a su vez mejora el valor percibido por el cliente de la experiencia de compra y aumenta la disposición a pagar en tiendas con tecnología de control de multitudes integrada. El estudio también amplía la aplicación de la Teoría de la Gestión del Terror en un nuevo contexto.

漫长的销售期（即圣诞节时间、黑色星期五等）和购物时的传染风险（即在COVID-19等大流行病期间）显示了拥挤的购物环境对消费者行为的负面影响程度。 因此, 利用恐怖管理理论（TMT）和刺激-组织-反应（S-O-R）方法, 我们建立了一个新的模型来研究人群检查技术对购物焦虑、购物体验的感知价值和支付意愿的影响。

在一家独立研究公司的帮助下, 我们采用横断面研究设计, 从居住在英国的个人中收集了1000份有效的答复。

结果显示, 人群检查技术提示减少了购物焦虑, 改善了价值认知, 并提高了支付意愿。此外, 技术在减少购物焦虑方面的功效受到顾客购物取向的调节。

这项研究是第一个调查在消费者旅程的初始阶段使用的人群监测系统, 以实时显示店内消费者的数量。它为零售业技术应用的文献做出了贡献, 提供了技术线索减少购物焦虑的证据, 这反过来又提高了顾客从购物体验中感知到的价值, 并增加了在有嵌入式人群检查器技术的商店中的支付意愿。该研究还扩展了恐怖管理理论在新环境中的应用。