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As China’s e-commerce and cross-border e-commerce rapidly develop, the cross-border e-commerce supply chain exhibits characteristics of globalized development scale, collaborative multiparty participation, streamlined management processes, digitalized production and trade and flexible strategic choices. It tends toward data-driven intelligence, interoperable information collaboration, personalized order responses, sustainable supply chain management and secure blockchain technology. These characteristics and trends provide critical references for businesses, governments and investors.

In response to issues such as inconsistent legal regulations, imbalanced logistics and transportation, imperfect payment settlements and opaque supply chains.

It is recommended to take measures to strengthen cooperation and communication, optimize logistics, reduce customs clearance difficulties, reinforce safeguard measures and promote sustainable development, collectively fostering the healthy growth of cross-border e-commerce.

With the rapid development of cross-border e-commerce, green and low-carbon initiatives have become a significant trend in this sector. The cross-border e-commerce supply chain refers to the mechanism that reduces environmental impacts and enhances resource efficiency from manufacturers to consumers. It primarily involves manufacturers, e-commerce platforms, logistics companies and payment and settlement processes. The cross-border e-commerce supply chain is gradually becoming a highlight in China’s foreign trade, supporting the concept of “buying globally and selling globally” and connecting the “world’s factory” with the “world’s market.”

Drawing on the social presence theory, this study aims to explore how supplier–customer social media interactions influence supplier observers’ trust in the customers and what mechanisms contribute to variation in trust experience.

A total of 36 semi-structured interviews were conducted with Chinese suppliers using WeChat for business-to-business interactions. Data were analyzed in three steps: open coding, axial coding and selective coding.

Findings reveal that varied trust is based not only on the categories of social presence of interaction – whether social presence is embedded in informative interactions – but also on the perceived selectivity in social presence. Observer suppliers who experience selectivity during social and affective interactions create a perception of hidden information and an unhealthy relationship atmosphere, and report a sense of emotional vulnerability, thus eroding cognitive and affective trust.

The findings contribute new understandings to social presence theory by exploring the social presence of interactions in a supplier–supplier–customer triad and offer valuable insights into business-to-business social media literature by adopting a suppliers’ viewpoint to unpack the mechanisms of how social presence of interaction positively and negatively influences suppliers’ trust and behavioral responses.

The main purpose of this paper is to examine the adoption of big data analytics (BDA) in the Tanzania banking industry by investigating the influence of technological, environmental and organizational (TOE) factors while exploring the moderating role of perceived risk (PR).

The study employed a qualitative research design, and the research instrument was developed using per-defined measurement items adopted from prior studies; the items were slightly adjusted to fit the current context. The questionnaires were distributed to top and middle managers in selected banks in Tanzania using the snowball sampling technique. Out of 360 received responses, 302 were considered complete and valid for data analysis. The study employed partial least squares structural equation modeling (PLS-SEM) to examine the developed conceptual framework.

Top management support and financial resources emerged as influential organizational factors, as did competition intensity for the environmental factors. Notably, bank size and perceived trends showed no significant impacts on BDA adoption. The study's novelty lies in revealing PR as a moderating factor, weakening the link between technological readiness, perceived usefulness and the intent to adopt BDA.

This study extends literature by extending the TOE model, through examining the moderating roles of PR on technological factors. Furthermore, the study provides useful managerial support for the adoption of BDA in banking in emerging economies.

This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector.

From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure.

The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible.

Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

The demand for halal food products is increasing globally. However, fraudulent activities in halal products and certification are also rising. One strategy to ensure halal integrity in the food supply chain is applying halal blockchain technology. However, to date, a few studies have assessed the factors and variables that facilitate or hinder the adoption of this technology. Thus, this study aims to assess the significant factors and variables affecting the adoption of halal blockchain technology.

A Delphi-based approach, using semi-structured interviews, was conducted with three food companies (chicken slaughterhouses, milk processing plants and frozen food companies). The cognitive best–worst method determines the significant factors and variables to prioritise halal blockchain adoption decisions.

The results showed that the most significant factors were coercive pressure and halal strategy. Nineteen variables were identified to establish a valid hierarchical structure for halal blockchain adoption in the Indonesian food industry. The five significant variables assessed through the best–worst method were demand, regulator, supply side, sustainability of the company’s existence and main customers.

The proposed halal blockchain decision structure can assist food companies in deciding whether to adopt the technology.

This study proposes 19 variables that establish a valid hierarchical structure of halal blockchain adoption for the Indonesian food industry.

This study aims to assess the impact of determinants on the effectiveness of internal audit (IA) within the banking industry of Bangladesh.

The data was obtained through 152 survey questionnaires from a total of 43 privately owned and six state-owned commercial banks in Bangladesh. The analysis was conducted using structural equation modeling.

The findings demonstrate that the independence of internal auditors and the quality of IA substantially impact enhancing the efficiency of IA. On the other hand, the competence of internal auditors and management support in IA functions do not significantly impact the effectiveness of IA.

The study’s findings may have significant policy implications for the government, regulators, internal auditors, management committees and other stakeholders in establishing programmes to enhance the efficacy of IA as a component of banking audit management reforms.

This study makes three distinct contributions to the existing literature. Firstly, previous literature focused on the determinants affecting the external audit efficiency of the public companies and banking sectors in Bangladesh (Hasan, 2018; M. M. U. Reza, 2021). In this study, the author enhances the research by presenting empirical findings on the IA effectiveness of banks. Secondly, the author expands the research by incorporating both private and state-owned commercial banks as samples. Thirdly, the study is unique given that it investigates the effectiveness of IA in response to the recent financial scandals in the banking industry of Bangladesh (The Daily Star, 2023).

The study aims to identify the determinants of customer satisfaction in the electronic commerce (e-commerce) industry in Bangladesh. It also investigates whether acceptance of IT innovation mediates the relationship between the determinants of e-commerce and customer satisfaction.

A survey questionnaire had been designed and distributed among the customers of e-commerce businesses. Data were collected from 408 respondents, who were mostly from urban areas of the country. The collected data had been analysed with the application of the partial least square approach using SmartPLS4. First, the measurement model was applied to determine the validity and reliability of the dataset. Then, the structural model was utilized to justify the hypothesis.

The results showed that customer service, perceived ease of use and customer trust in e-commerce services have a significant positive impact on customer satisfaction. The acceptance of IT innovation, which showed a positive influence on customer satisfaction, enhanced customer satisfaction when accompanied by perceived ease of use and digital literacy.

The results would have valuable insight for the e-commerce business in designing their products and services and taking policies to achieve long-term customer loyalty.

This is the first study that incorporates IT innovation acceptance as a mediating variable. Although a number of factors have been identified as the determinants of customer satisfaction, the specific mechanism of IT innovation acceptance as a mediator between predictors and customer satisfaction is unique in this study.

This paper aims to explore the conditions in a business-to-business-to-consumer (B2B2C) context characterized by new technologies. Innovations enhance disintermediation and pursue sustainability goals that drive customers’ willingness to use eco-friendly delivery options, namely, parcel lockers – in e-commerce and their impacts in terms of communication and transparency along the supply network.

The study conducted an extensive survey in Italy and Germany, collecting 1,010 usable responses. Structural equation modelling was used to analyse the data with the aim of identifying the factors that drive customers’ willingness to use parcel lockers and the effect on customers’ behaviour as determined by the disclosure of information about the environmental performance of different delivery options.

The results highlight several factors affecting the willingness to use parcel lockers, namely, performance and effort expectancy, social influence, technology anxiety, hedonistic motivation and environmental knowledge. The results also demonstrate that the disclosure of information about the environmental performance of different delivery options influences customers’ behaviour.

This paper faces several limitations, mostly related to the focus on just two countries, the use of cross-sectional data and the survey’s explicit reference to just one type of product. Nevertheless, the findings contribute to the discussion on the relevance of information sharing along the supply chain, providing favourable evidence in this regard. It also improves the stream of research concerning technology adoption in the context of e-commerce, highlighting factors that can lead consumers to use eco-friendly self-service technologies.

The results can support companies in understanding how they can design and manage the last mile of delivery to jointly achieve customer satisfaction, process efficiency and superior environmental performance.

This pioneering contribution studies the adoption of delivery solutions for e-commerce and its implications for the supply network.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

The purpose of this paper is to investigate how complementors’ marketing capability and technology capability affect their performance. Drawing on social capital theory, the authors examine platform network centrality as a mediator and platform reputation as a moderator of the relationships between these two capabilities and complementor performance.

This study collects data by questionnaire from 154 Chinese firms adopting e-commerce platforms. Hierarchical multiple regression is used to test the hypotheses of this study.

This study finds that complementors’ marketing capability and technology capability positively affect performance by increasing their platform network centrality. Moreover, platform reputation positively moderates the relationship between platform network centrality and complementor performance, and it strengthens the mediating role of platform network centrality.

This paper emphasizes the critical role of marketing capability and technology capability on complementor performance. It explores the improvement path of complementor performance from the perspective of network position, which is a key element for complementors to effectively leverage their capabilities to build competitive advantage.