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This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail.

The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM).

The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions.

To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR.

This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI.

The rapid, yet low-profit, expansion of the production capacity of state-owned enterprises (SOEs) represents a remarkable phenomenon. However, the motivation behind this key operational decision remains underexplored, especially concerning the prioritization of sociopolitical and financial goals in operations management. Drawing on the multiple-goal model in the behavioral theory of the firm (BTOF), the authors' study aims to examine how SOE capacity expansion is driven by performance feedback regarding the sociopolitical goal of employment provision and how SOEs differently prioritize sociopolitical and financial goals based on negative versus positive feedback on the sociopolitical goal.

The authors' study uses panel data on 826 Chinese SOEs in manufacturing industries from 2011 to 2019. The authors employ the fixed-effects model with Driscoll–Kraay standard errors, which are robust to heteroscedasticity, autocorrelation and cross-sectional dependence.

The authors find that SOEs increase capacity expansion as sociopolitical feedback becomes more negative, but they may not increase capacity expansion in response to positive sociopolitical feedback. Moreover, negative profitability feedback strengthens SOEs' capacity expansion in response to negative sociopolitical feedback. In contrast, negative profitability feedback weakens their response to positive sociopolitical feedback.

The authors' study offers a novel behavioral explanation of SOEs' operational decisions regarding capacity expansion. While the literature has traditionally assumed multiple goals as either hierarchical or compatible, the authors extend the BTOF's multiple-goal model to illuminate when firms pursue sociopolitical and financial goals as compatible (i.e. the activation rule) versus hierarchical (i.e. the sequential rule), thereby reconciling their tension in distinct performance situations. Practically, the authors provide fine-grained insights into how operations managers can prioritize multiple goals when making operational decisions. The authors' study also shows how policymakers can influence SOE operations to pursue sociopolitical goals for public benefit.

Accurate and timely cost prediction is critical to the success of construction projects which is still facing challenges especially at the early stage. In the context of rapid development of machine learning technology and the massive cost data from historical projects, this paper aims to propose a novel cost prediction model based on historical data with improved performance when only limited information about the new project is available.

The proposed approach combines regression analysis (RA) and artificial neural network (ANN) to build a novel hybrid cost prediction model with the former as front-end prediction and the latter as back-end correction. Firstly, the main factors influencing the cost of building projects are identified through literature research and subsequently screened by principal component analysis (PCA). Secondly the optimal RA model is determined through multi-model comparison and used for front-end prediction. Finally, ANN is applied to construct the error correction model. The hybrid RA-ANN model was trained and tested with cost data from 128 completed construction projects in China.

The results show that the hybrid cost prediction model has the advantages of both RA and ANN whose prediction accuracy is higher than that of RA and ANN only with the information such as total floor area, height and number of floors.

(1) The most critical influencing factors of the buildings’ cost are found out by means of PCA on the historical data. (2) A novel hybrid RA-ANN model is proposed which proved to have the advantages of both RA and ANN with higher accuracy. (3) The comparison among different models has been carried out which is helpful to future model selection.

The purpose of this study is to apprise mobile loyalty to halal food purchasing, including food quality, mobile quality, perceived value and satisfaction as its causes, and analyze the halal trust and health risk moderating role on the connections between mobile loyalty and its determinants.

A total of 307 responses from millennial Muslims were collected from the Bandung region of Indonesia via an online survey. Partial least squares modeling was applied to review the proposed mobile loyalty model.

This research found that the mobile loyalty model integrating halal food quality, mobile service quality, perceived value and satisfaction has satisfactory goodness of fit. The research confirms the function of mobile service quality but not halal food quality as drivers of mobile loyalty. Next, this study suggests that halal trust and health risks do not moderate the association between mobile loyalty and its determinants.

This study recommends that managers devote resources to upgrading the quality of their mobile apps to build loyalty. Offering high-quality halal food is also an important driver of millennial Muslim satisfaction.

To the best of the authors’ knowledge, this research is the first to investigate mobile loyalty in halal food.

This study explored the influence of Dervin’s sensemaking methodology (SMM).

Citation context analysis was used to identify the most influential SMM concepts in 948 articles citing 34 SMM-related studies by Dervin that were published between 1983 and 2017. Moreover, the bibliometric method and content analysis were incorporated to examine the disciplines and research topics influenced by the SMM-related studies and the role of cited content in SMM-related studies.

The influence of SMM is concentrated in information behavior research in the field of library and information science (LIS). The 1992 book chapter From the mind’s eye of the user was most frequently cited, followed by the first SMM study from 1983; 14 of the 18 content categories were relevant to SMM. “Sensemaking,” at the core of SMM, was the most influential cited concept, primarily cited from the 1983 SMM-related study. Although the SMM was developed as a research method, it has not been primarily applied to design research methods in other studies.

This study explored the interdisciplinary influence of Dervin’s SMM from several aspects and demonstrated the complex information dynamics between SMM-related works and citing articles.

This study aimed to identify a specific taxonomy of entry modes for international construction contractors and to develop a decision-making mechanism based on case-based reasoning (CBR) to facilitate the selection of the most suitable entry modes.

According to the experience orientation of the construction industry, a CBR entry mode decision model was established, and based on successful historical cases, a two-step refinement process was carried out to identify similar situations. Then the validity of the model is proved by case analysis.

This study identified an entry mode taxonomy for international construction contractors (ICCs) and explored their decision-making mechanisms. First, a two-dimension model of entry mode for ICCs was constructed from ownership and value chain dimensions; seven common ICC entry modes were identified and ranked according to market commitment. Secondly, this study reveals the impact mechanism of the ICC entry mode from two aspects: the external environment and enterprise characteristics. Accordingly, an entry mode decision model is established.

Firstly, sorting out the categories of entry mode in the construction field, which provide an entry mode list for ICCs to select. Secondly, revealing the impact mechanism of ICC entry mode, which proposes a systematic decision-making system for the selection of ICC entry mode. Thirdly, constructing a CBR entry mode decision-making model from an empirical perspective, which offers tool support and reduces transaction costs in the decision-making process.

The study on entry modes for ICCs is still in the preliminary exploratory stage. The authors investigate the entry mode categories and decision-making mechanisms for ICCs based on Uppsala internationalization process theory. It widens the applied scope of Uppsala and promotes cross-disciplinary integration. In addition, the authors creatively propose a two-stage retrieval mechanism in the CBR model, which considers the order of decision variables. It refines the influence path of the decision variables on ICCs' entry mode.

This study examines green absorptive capacity as an important intervening variable that elucidates the relationship between green supply chain management (GSCM) practices (specifically, green purchasing, customer cooperation and investment recovery) and firm performance.

Drawing from the theoretical underpinnings of the natural-resource-based view theory and information processing theory, a research model is developed and tested using data obtained from 368 manufacturing firms in Ghana. Data analysis was conducted using structural equation modeling.

The results indicate that green purchasing, customer cooperation and investment recovery have a direct positive and significant effect on firm performance. Additionally, green purchasing and customer cooperation have a positive and significant effect on green absorptive capacity but investment recovery does not. Further, the results show that the paths from green purchasing and customer cooperation to firm performance are positively mediated by green absorptive capacity.

The study reveals to supply chain managers that green absorptive capacity is an important conduit through which firms can achieve enhanced firm performance from GSCM initiatives.

This study makes a contribution by integrating the absorptive capacity literature and green management literature and establishes green absorptive capacity as a mechanism through which GSCM practices enhance firm performance.

The purpose of this paper is to assess the validity and utility of two theoretical approaches to understanding the relationship between strategic orientations, innovation and firm performance and to examine the role of innovation in the relationship while avoiding circular arguments. The universalistic approach suggests that strategic orientations have independent and parallel effects on firms’ performance, and that innovation does not influence this relationship. The holistic approach proposes that strategic orientations in a complementary and interrelated view have both direct and indirect effects on firms’ performance through innovation.

A meta-analytic path analysis applying two-stage structural equation modeling (TSSEM) was conducted on data from 132 primary studies and 33,063 observations.

The holistic approach was demonstrated to be superior due to its more explanatory power in linking more complex relationships through simultaneous direct and indirect effects and its capacity for including the interrelatedness and complementarity of strategic orientations. It was found that innovation has a full mediating role in the relationship between entrepreneurial orientation (EO) and firm performance, and a partial mediating role in the relationship between market orientation (MO) and learning orientation (LO) and firm performance.

The study used observed variables instead of latent variables for meta-analytic path analysis, which may reduce some sources of endogeneity. However, causal inference is not possible due to the nature of meta-analysis. The scope of the final sample was limited by some studies not reporting the estimates of correlations between constructs.

Managers can improve an organization's chances of success in the marketplace by adopting a holistic view of strategic orientations focusing on customer satisfaction, learning from the external environment and pursuing new market opportunities. Furthermore, an organization can gain a competitive advantage through innovation by creating products and services that are different from what is currently available in the market. To be successful, an organization must not only create innovative products and services but also market them effectively to consumers.

This study is the first to meta-analytically assess the explanatory value of two theorized models linking strategic orientations, innovation and firm performance. It also clarifies the role of innovation in the relationship between strategic orientations and firm performance.

This exploratory research aims to identify the effect of perceived stress level and self-efficacy on management quality and what practices and theories need to be enhanced to improve management quality under volatility business environments.

The study surveyed 291 working women, using the Perceived Stress Scale and the General Self-Efficacy Scale. Latent class analysis (LCA) for classifications of respondents, using categorical observed variables and MANCOVA, are applied to determine the relationship between stress and self-efficacy on the assigned classes.

The study suggests that in a highly volatile business environment, where stress is high, affecting management quality, managers as individuals fall into one of four classes that describe their techniques of coping with the stress, namely Uncommitted Experimenters, Try Anything, Intrinsically Motivated and Externally Motivated. Techniques of stress management classification are significantly related to the combined perceived stress and self-efficacy measures, with Externally Motivated respondents as the classification with a significant mean difference.

The main limitation of the study at hand refers to the sample size versus the number of potential factors of stress. This limitation highlights the need for further data gathering and research in this area, as stress is a critical factor of performance and often ignored in traditional management theories. Another limitation of this study is the lack of in-depth analysis of the use of meditation; its benefits and how to best use this practice in traditional work settings.

The outcome of the study could have significant implications for quality of management in business, private and social sectors by providing meditation as a tool for employees and stakeholders to handle stress in conflict zones.

Using stress management techniques might prove to be a low-cost tool for better quality management of human assets.

The authors study focuses on women in volatile economic turmoil, natural devastations, conflict areas and politically insecure environments. This socioeconomic segment was rarely scrutinized despite its direct effect on a large number of economies hosting a sizeable portion of the world’s population. Interesting potential results highlight the relationship between the respondents in the Intrinsically Motivated class and stress reduction for the benefit of management quality.

Thus, this study aims to determine the status-quo of research on the role of IT in M&A from 2010 to 2022 by providing a summative meta-analysis of this phenomenon.

This study presents a meta-analysis of mergers and acquisitions (M&A) research in information systems (IS), aimed at accounting for themes in M&A literature over the past 13 years, research methodology, research frameworks, level of analysis and geographical distribution. A total of 47 articles from 24 peer review articles and 23 conference publications were analyzed from 2010 to 2022.

Findings of the study suggest that M&A research in IS emphasizes IS integration at the expense of other under-explored dimensions such as M&A context, stakeholder involvement and within-firm conditions. Although studies on M&A have increased over the past 10 years, a significant number of studies have not been underpinned by models and theories. Also, a large number of studies adopted the qualitative approach as research methodology compared to quantitative, design science and mixed methods.

This study contributes to the literature on M&A in IS by proposing an M&A in IS research framework that bridges the gap between existing and future studies on M&A in IS research by shedding more light into well research areas and opportunities for further studies.