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This paper investigates how individuals' decision-making approach and perceptions of a game's cognitive realism affect the performance of virtual businesses in a web-based simulation game.

Survey data are collected from 274 business simulation game users and is analysed using the fsQCA technique.

The study identifies three alternative pathways to high and low performance in a business simulation game. Results indicate that a flexible decision-making approach exists in all high performance pathway solutions. Where a game is perceived to be realistic, a more focused decision-making approach is associated with high performance. However, where perceived cognitive realism is absent, a less focused experimental decision-making approach is employed, which increases the chances to achieve low performance. Finally, perceived cognitive realism and an experimental decision-making approach are found to be mutually exclusive for achieving high performance.

Whilst the learning benefits of web-based simulation games are widely acknowledged, the complex interplay amongst factors affecting performance in games is under-researched. Limited research exists on how perceptions of a game's cognitive realism interact with user decision-making approaches to affect performance.

This study aims to explore sustainable development and business success (BS) through decision-making (DM) in Pakistan’s circular economy.

This is a co-relational study in which the researchers used cross-sectional data collected from the managers of Pakistan’s manufacturing industries. Accordingly, the authors based this study’s findings on 373 valid samples.

This study’s structural equation modeling results reveal that DM has a positive and significant effect on sustainable development, which comprises competitiveness, business performance enhancement, flexibility, customer satisfaction and technology development. Moreover, DM positively and significantly affects BS.

This study’s findings support sustainable development, strengthen the socioeconomic conditions and bring about the industries’ well-being through DM. In addition, these findings demonstrate the need for the circular economy to tackle industrial challenges and simultaneously open up economic and environmental growth opportunities for society.

This study offers the original contribution from a circular economy perspective; there needs to be more empirical evidence among managers of manufacturing industries. Besides, this study provides DM’s role in achieving sustainable development in the presence of BS, which has disappeared in an integrated way, particularly in a circular context.

This study aims to empirically investigate the relationship between artificial intelligence (AI) in marketing (AIM) and business performance from the resource-based view (RBV) perspective.

A survey strategy was used in this study to collect data from 225 small and medium enterprises (SMEs) respondents who were on the registered list of the Ghana Enterprise Agency in the Eastern Region of Ghana. Structural equation modeling – path analysis was used to estimate the impact of AIM on the performance of SMEs.

The analyzed data shows that AIM has significant impact on the financial performance, customer performance, internal business process performance and learning and growth performance in the case of SMEs in Ghana. This study establishes the significance of AIM approach in achieving financial performance, customer performance, internal business process performance and learning and growth performance through the application of AIM determinants including, Internet of Things (IoT), collaborative decision-making systems (CDMS), virtual and augmented reality (VAR) and personalization.

Aside the aforementioned significance of this research study, this study has limitations. The sample size of this research study can be expanded to include SME respondents in other geographical areas that were not considered in this study. Future research studies should concentrate on how AIM can analyze customer communications and information such as posts on social media to develop future communications that may enhance customer engagement.

The practical implications comprise of two key items. First, this research study encourages SME owners and managers to develop an AIM method as a fundamental strategic goal in their pursuit to improve SME performance. Second, SME owners and managers should increasingly implement the four determinants of AIM indicated in this research study (i.e., IOT, CDMS, VAR and personalization) to develop essential resources for effective application of AIM to improve their performance.

The results of this study provide a strong support to RBV theory and the proposition that AIM and its determinants (i.e., IOT, CDMS, VAR and personalization) should be recognized as an essential strategic resource for improving the performance (i.e., financial performance, customer performance, internal business process performance and learning and growth performance) of SMEs. This study also contributes to the current body of knowledge on AIM and management, particularly in the context of an emerging economy.

The purpose of this study is to examine the factors that affect managers’ ethical decision-making in export-oriented readymade garments in Bangladesh.

This is an empirical study based on the quantitative approach undertaking a cross-sectional survey method where a convenience sampling technique was applied. The analysis was done using partial least square structural equation model applying Smart-PLS version 3.0.

This study confirmed that all the components of cognitive appraisal processes, including perceived severity, perceived vulnerability, response efficacy and self-efficacy, have a significant influence on attitude. Attitude, in turn, mediates the relationship between these variables and the behavioural intention of ethical practice, except for perceived vulnerability. Besides, moral obligation is found to mediate the relationship between attitude, self-efficacy and the behavioural intention of ethical decision-making. The study also found that ethical climate and subjective norms have a direct influence on behavioural intention. Furthermore, behavioural intention, ethical climate and self-efficacy are positively related to actual decision-making behaviour. However, this study did not find any direct effect of subjective norms on moral obligation.

The organization should include an emphasis on building ethical culture and setting an ethical code of conduct within the organization to sustain ethical practice within employees. However, the practitioner should work on enhancing self-efficacy to curb unethical practices by individuals.

This research contributes to the management of garments manufacturers by a practical and theoretical understanding of what influences the ethical behavioural decision-making process. Valuable guidelines are provided on the ethical decision-making process in the garments manufacturing companies for future researchers.

Decision-making competence (DMC) of entrepreneurs and managers is a longstanding topic in this increasingly globalized world. These figures operate in conditions not within their own control, and good levels of DMC are often considered to be desirable for the flourishing of business and society. This paper reports an empirical investigation on the DMC of entrepreneurs and managers, in an attempt to inform about their tendencies to incur in risky and costly choices.

Three cognitive biases associated with operational strategies and individual characteristics of entrepreneurs and managers, namely under/overconfidence (UOC, i.e. self-confidence in taking decisions), resistance to sunk costs (RSC, i.e. propensity to take cost investments) and consistency in risk perception (CRP, i.e. how well individuals understand probability rules) were considered . Cognitive biases measures were used in a cross-sectional study on a sample of n = 639 entrepreneurs and n = 512 managers. Data collected via online survey were analyzed using descriptive statistics and inferential statistics to determine differences among entrepreneurs and managers DMC.

Analyses reveal that entrepreneurs exhibit higher levels of UOC compared to managers with a marked presence of UOC among entrepreneurs at younger ages. Conversely, performance regarding RSC improves with higher education levels while age and RSC are positively correlated only for managers, regardless of education. Lastly, entrepreneurs and managers resulted as not being affected by CRP. This study discusses these results to provide initial insights for further avenues of research and practice.

The study offers an innovative, evidence-based viewpoint on how entrepreneurs and managers deal with risky and costly decisions. It offers an initial understanding of the role of UOC, RSC and CRP, that is specific cognitive biases associated with operational strategies and individual characteristics, in the DMC of these working figures. The study forwards avenues of scrutiny of quick-witted entrepreneurs and systematic managers.

The present study shows that the implementation and development of enterprise resource planning (ERP) systems as a technological innovation provide a competitive advantage that helps to improve the functionality of business intelligence (BI) systems in the digital transformation of manufacturing companies, in addition to improving overall firm performance.

The research uses the structural equation approach based on PLS-SEM technique with a sample of 120 firms in the manufacturing industry in Coahuila, Mexico.

The paper provides empirical insights into how the interaction of ERP systems and innovation significantly affects the functionality of BI Systems and has a substantial effect on overall firm performance.

Empirical evidence of how advanced digital management systems (ERP and BI) impact digitalization processes in organizations by improving performance is still scarce.

Based on the dynamic capability view, this study aims to draw for the first time the missing link between big data analytics capabilities (BDAC) on both green absorptive capacity (GAC) and green entrepreneurship orientation (GEO). It is theoretically necessary to address how BDAC levels up the GAC to achieve the same level of GEO and then respond to their green business agenda. In addition, the study introduces knowledge sharing (KS) and green organizational ambidexterity (GOA) as potential moderating factors in the relationship between GEO and eco-innovation and explores the mediation role of GAC in the BDAC–GEO relationship.

The study collected 268 questionnaires from employees working in Chinese manufacturing firms using a self-administered survey and cross-sectional research design. The study applied SmartPLS to analyze the obtained data.

The findings revealed that BDAC positively and significantly influences GAC and GEO, positively impacting eco-innovation. The KS and GOA's moderation effect strengthens the relationship between GEO and eco-innovation. GAC partially mediates the relationship between BDAC and GEO.

The study advises firms to invest heavily in developing technological aspects of BDAC as a dynamic strategic capability that facilitates tracking and anticipating the future behavior changes of customers, competitors and market demands. BDAC also allows firms to upgrade and reconfigure their dynamic capabilities by responding to managerial, operational and strategic necessities. BDAC is necessary to increase GAC's impact and help drive GEO's eco-business agenda. Notably, the study gave superior attention to KS and GOA as a backbone of GEO to improve eco-innovation economic and managerial outcomes.

The study highlights the necessity to upgrade and integrate technological aspects of BDAC within firms' GEO to enhance green practices. Significantly, green business practices changed quickly as customers' needs and eco-markets fluctuated; BDAC is the crucial dynamic capability fostering GAC and entrepreneurs' green mindset to deal with environmental challenges. To the best of the author’s knowledge, this study is to predict the potential effect of BDAC on both GAC and GEO. BDAC helps firms to develop GEO eco-business agenda and balance green growth with green issues.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).

The use of innovative technologies by firm employees is a key factor in ensuring the competitiveness of firms. However, researchers and practitioners have been concerned about the willingness of technology end users to use innovative technologies. This study, therefore, aims to determine the factors affecting the intention to use marketing analytics technology.

This study surveyed 213 firm employees. The quantitative data collected was analysed using partial least squares structural equation modelling.

The results reveal that performance expectancy, facilitating conditions, attitudes and perceived trust have a positive and significant effect on intentions to use marketing analytics. Effort expectancy, social influence and personal innovativeness in information technology were found not to predict intentions to use marketing analytics.

This study has practical implications for firms seeking to enhance the use of marketing analytics technology in developing countries.

This study contributes to the use of UTAUT, perceived trust, personal innovativeness and user attitude in predicting the intentions to use marketing analytics technology.

Textile and contemporary apparel manufacturers are adopting and integrating cutting-edge technologies to reduce their impact on the environment and gain an advantage in the marketplace. Most previous studies have ignored business intelligence systems (BIS), notably in the textile and apparel industry (T&A), in favor of looking at the larger picture of how big data would affect retail and distribution in a company. This is especially true for the T&As.

The authors report that they conducted 14 semi-structured interviews with 12 international luxury tourism service providers. In this case, researchers use snowball features and systematic techniques to select participants. A qualitative content analysis strategy is used to capture the focus of the interviews.

Problems with T&A company sustainability, opportunities to increase value creation via use of industry-leading business intelligence (BI) solutions and perceived roadblocks to BIS adoption were all found by the poll. Garment retail and distribution sector has benefited greatly from the increased use of Industry 4.0 technologies, especially those that provide better BI solutions. Determine the extent to which industry participation slows down or speeds up the process. The Company Information System (BIS) will help convince non-tech-savvy business owners of the financial, economic and environmental benefits of adopting certain technologies developed as part of the industry 4.0 movement.

The authors of this research claim theirs is one of the first to investigate what variables affect the uptake of BIS, ultimately hoping to find out how BIS may be used by T&A businesses to tackle environmental issues through the use of Industry 4.0 technologies. The purpose of this study was to see whether BIS might aid T&A firms with their sustainability issues.

In the last several years, there has been a meteoric rise in interest in big data and business analytics among firms and educational institutions alike. This paper tries to introduce readers to the concept of business analytics in a way that is both academic and accessible, considering both the present and future of the field. This paper begins with a quick introduction, followed by a summary of the three distinct forms of predictive modeling discussed.

In an effort to help aspiring analytics professionals, they have identified, categorized and evaluated the nine distinct players that are now active in the analytics market. Following this, they will provide a high-level summary of the many different research projects currently being worked on by their group.