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The purpose of this empirical study is to consider the interaction of self-service technologies (SSTs) with retail customers, exploring how retail customers perceive SST value and how this value affects their choice confidence when shopping.

We carried out a large shopper survey in collaboration with six French mass retailers. Digital kiosks and interactive tablets were the focal SSTs. Partial least squares-path modelling (PLS-PM) was used to test our cost‒benefit conceptual framework and the corresponding research hypotheses. Furthermore, through multigroup comparison analysis, we tested the moderating effect of customers’ subjective knowledge of the product category.

Functional and interactive benefits/costs arising from SST usage determine customer perceived value. The key notion of perceived SST value implies that people make favourable cost‒benefit tradeoffs. Customer choice confidence is positively affected by perceived SST value. Customer product category knowledge plays a key role as a moderator of human–SST interactions in phygital retail settings.

This paper is concerned with the role of SST in creating phygital experiences and delivering value to retail customers. This is a first attempt at examining how perceived SST value affects customer choice confidence and what role customer product category knowledge plays.

Continuous development of digital technology makes it necessary for digital entrepreneurs to pivot to cope with the environmental changes. However, limited research has focused on the important strategic orientation of digital new ventures in digital contexts, digital orientation, which depicts the tendency of new ventures to utilize digital technologies to create value. This research aims to explore the relationship between digital orientation and pivoting, along with the mediating role of dynamic capabilities as essential organizational competencies. Additionally, the study investigates the influence of boundary conditions related to the environmental dynamism and the prior experience of entrepreneurs.

The data of this study were gathered by a two-phase survey of 328 Chinese digital new ventures in China with the assistance of entrepreneurial service organizations, entrepreneurship parks and entrepreneurial training institutions. The current study used regression analysis to verify the hypotheses and factor analysis to evaluate the validity and reliability of the measurement by using MPLUS, SPSS and PROCESS macro.

The findings of this research indicate that digital orientation enhances pivoting of digital new ventures, with dynamic capabilities acting as a crucial mediator in this process. Additionally, the dynamic environment and prior entrepreneurial experience influence both the relationship between digital orientation and dynamic capabilities, as well as the mediating effect of dynamic capabilities.

This study significantly contributes to the existing literature by exploring the relationship between digital orientation and pivoting in digital new ventures. This broadens the scope of research on pivoting and enriches the literature on digital orientation in the digital context. By emphasizing how these factors shape pivoting, our research provides valuable guidance for entrepreneurs responding to the dynamic environment and technological advances.

This research illuminates the relationship between digital orientation and pivoting based on the resource-based view (RBV) and dynamic capabilities theory (DCT). It explores the antecedent of digital orientation on digital new ventures’ pivoting activities, reveals the internal mechanisms and boundary conditions and enriches the literature related to RBV and DCT in the digital entrepreneurship context.

This research aims at investigating how business process management capabilities (BPMC) impact the effectiveness of sustainable digital transformation (ESDT). Furthermore, it delves into the mediation of dynamic decision-making (DDM) in the relationship between BPMC and ESDT.

This research employed the hypothetico-deductive technique. The statistical database was generated from sample of 712 respondents from small and medium companies (SMEs) in Vietnam, utilizing convenience and snowball sampling methods. The two-step process utilizing structural equation modeling, supported by SmartPLS version 4.1.0.9 and AMOS 28, was employed to assess the measurement model, while SmartPLS version 4.1.0.9 was used to evaluate the structural model.

The results of the analysis emphasize significant and positive correlations between the proposed constructs related to significance and effect size. The statistical results indicated that BPMC had a significant and beneficial effect on ESDT. This relationship was partially mediated by DMM.

The salient point emphasized that practitioners should prioritize enhancing focus on BPMC and DDM, as this would significantly facilitate more comprehensive solutions, enabling SMEs to achieve optimal success in sustainable digital transformation. Policymakers and government influencers are urged to concentrate on innovative attributes and ensure a conducive environment for the implementation of innovation by enacting regulations that promote the application of digital technology.

The findings of this study will broaden scholars’ understanding of the influence of BPMC on ESDT. The originality of the research is to provide research directions for advancing studies on the role of DDM in the context of sustainable digital transformation.

While big data analytics can spur innovation among firms, it is unclear whether it can effectively drive value creation, value proposition, value delivery and value capture to deal with disruptions and the ever-changing demands of customers. This study therefore aims to examine how value creation, value proposition, value delivery and value capture can be improved through big data analytics capability (BDAC). This study advances the discourse by investigating how the market environment and strategic orientations play significant but little-studied roles in enhancing or lessening BDAC’s impact on business model innovation (BMI).

Drawing on dynamic capability and contingency perspectives, a model of five hypotheses was developed and validated using survey data from 208 managers of manufacturing firms in Ghana. Covariance-based structural equation modeling was used for the analysis.

The findings revealed that BDAC and strategic orientation (market and learning) directly influence the dimensions of BMI (value creation, value proposition, value delivery and value capture). The findings further showed that strategic orientations partially mediate the BDAC–BMI link. The authors also noted that the BDAC–BMI link is amplified at high levels of market dynamism.

The findings suggest that investing in BDA alone may not be sufficient to drive superior business model innovation. However, market orientation and continuous learning are crucial to fully realizing BDAC’s full potential in enabling value creation, value proposition, value delivery and value capture, especially in a dynamic market environment.

This study contributes to existing BMI literature by being the first to examine how BDAC facilitates value creation, value proposition, value delivery and value capture in developing countries. This paper also advances BM literature by theorizing and validating important but rarely studied roles of strategic orientations and market dynamism. Thus, this paper extends the understanding of the conditions and mechanisms through which the effect of BDAC on value creation, value proposition, value delivery and value capture can be optimized.

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.

In order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.

The paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.

This study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study is to develop a comprehensive assessment of urban flood risk in the Hubei Province of China, focusing on the following three issues: (1) What are the factors that cause floods? (2) To what extent do these factors affect flood risk management? (3) How to build an effective comprehensive assessment system that can be used to reduce flood risk?

This study combines expert opinion and evidence from the extent literature to identify flood risk indicators across four dimensions: disaster risk, susceptibility, exposure and prevention and mitigation. The Criteria Importance Through Intercriteria Correlation (CRITIC) and the Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making approach were applied to calculate the weighting of factors and develop a model of urban flood risk. Then, ArcGIS software visualizes risk levels and spatial distribution in the cities of Hubei Province; uncertainty analysis verified method accuracy.

The results show that there are significant differences in the level of urban flood risk in Hubei Province, with cities such as Tianmen, Qianjiang, Xiantao and Ezhou being at high risk, while cities such as Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan and Huanggang are at lower flood risk.

The innovative method of combining CRITIC-GRA-TOPSIS reduces the presence of subjective bias found in many other flood risk assessment frameworks. Regional data extraction and uncertainty analysis enhance result reliability, supporting long-term decision-making and urban planning. Overall, the methodological approach developed provides an advanced, highly effective and efficient analysis and visualization of flood risk. This study deepens the understanding of flood risk assessment mechanisms and more broadly supports the development of resilient cities.