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The purpose of this paper on the level of sustainability of the oxbow lake is to determine the sustainability status, leverage of attributes and driving factors in the management of the oxbow lake in Buluh Cina Village in Kampar, Riau, Indonesia.

The types of data collected include primary data and secondary data. The data were collected using the methods of surveys, library research, laboratory analysis and interviews. The analysis methods employed in this research were the multidimensional scaling (MDS) analysis and the prospect analysis. The sustainability analysis was undertaken using the approach of the MDS analysis with the assistance of software RapOxbow.

The current sustainability status of the management of Lake Baru ecosystems according to a number of dimensions is regarded as sustainable with a sustainability index value by 50.95. Meanwhile, analysis results of each dimension show that the sustainability index for the ecological dimension is 42.56 and the sustainability index for the economic dimension is 47.44, which means that they are less sustainable. While the sustainability index for the socio-cultural dimension is 54.81, the sustainability index for the technological dimension is 53.12 and the sustainability index for the legal-institutional dimension is 56.83, meaning that they are fairly sustainable.

The originality of this paper lies at the approaches of this research which are MDS analysis and a prospect analysis, and the research location in Buluh Cina Village in Kampar, Indonesia, that has not been researched before. This is one of few studies which investigate comprehensively the sustainability analysis of management, especially in ecological, economic and socio-cultural dimensions in Indonesia.

This paper aims to examine whether CEO succession with gender change (male to female) affects audit fees in the Chinese setting. In addition, this study examines whether the relationship exists in both types of ownership, i.e. non-state-owned enterprises (SOEs) and SOEs.

This study uses data from all A-share non-financial firms listed on both the Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE) for the period 2009 to 2015. To draw inferences, this study uses pooled ordinary least squares regression as a baseline technique. This study performs sub-sample analyzes for robustness. To account for endogeneity, this study uses three techniques including firm fixed-effects regression, the two-step Heckman model and the system generalized method of moments (GMM).

This study documents a significantly negative relationship between CEO succession with gender change and audit fees. However, the negative effect of CEO succession on audit fees is more pronounced in non-SOEs than SOEs. This study also finds, in additional analyzes, a strong negative effect of female CEO succession on audit fees in sub-sample of large, high-risk, high-performance and firms audited by non-big auditors. The main finding is robust across three endogeneity techniques.

The findings add to the ongoing debate about the underrepresentation of women in key executive positions such as CEO. The results suggest that CEO succession from male to female has a favorable effect on the quality of internal monitoring mechanisms (due to the superior monitoring skills of women) and enhances the quality of financial reporting. The study has practical implications for regulatory bodies and corporate decision-makers; this study encourages them to look into considering women in the executive succession framework.

This study contributes to the literature by exploring the effect of CEO succession with gender change (male to female) on audit fees in the context of China and the existence of this relationship in non-SOEs and SOEs.

The present study aims to develop a strategic business performance (SBP) model for larger firms by examining the mediating role of structural flexibility in the network capability–SBP link, as well as testing the moderating role of entrepreneurial orientation in the relationship between structural flexibility and SBP.

Data were collected from 929 senior managers/owners of large textile sector firms operating in Pakistan. Regression and bootstrapping techniques were used to test the proposed relationships.

The results revealed that network capability positively shapes firms' structural flexibility, which, in turn, helps firms achieve SBP. The present work also showed that entrepreneurial orientation strengthens the positive relationship between structural flexibility and SBP.

This study is based on the cross-sectional data, and data were collected from the textile sector firms operating in Pakistan.

The findings suggest that managers should focus on developing firms' network capability, which positively shapes structural flexibility and helps firms achieve SBP. Entrepreneurial orientation can also play an imperative role for strengthening the link between structural flexibility and SBP.

The value of the present work rests on the deeper understanding of the network capability–SBP link that it offered by examining the relationships of the network capability dimensions with SBP through structural flexibility. Moreover, by bringing to the fore firms' entrepreneurial orientation as a moderator of the structural flexibility–SBP relationship, the study provided a new vantage point to uncover the complexities involved in the links between network capability, structural flexibility, and SBP.

This study aims to examine how positive supervisory support plays a role in attenuating employees’ knowledge-hiding behavior via the underlying mechanism of psychological ownership and workplace thriving. Integrating the social information processing perspective and conservation of resource theory, this study suggests that due to the mediating role of employee psychological ownership and workplace thriving, positive supervisor support may negatively affect knowledge-hiding behavior.

Hypotheses were tested with multiwave three-round survey data collected among 432 individuals in various Pakistani hotels.

This study found that supervisory support attenuated knowledge-hiding behavior by enhancing psychological ownership and workplace thriving serially. As expected, the supportive conduct of the supervisor positively influenced psychological ownership which, in turn, helped workplace thriving and eventually influenced employees’ knowledge hiding.

This study contributes to the extant body of knowledge on knowledge hiding by highlighting a significant antecedent that supervisory support may be instrumental in discouraging knowledge hiding. Furthermore, this study detailed an underlying serial mediating mechanism in the shape of psychological ownership and workplace thriving that connects supervisory support with reduced knowledge hiding.

This study aims to investigate the question concerning whether tournament incentives motivate chief executive officers (CEOs) to be socially responsible.

Data from all A-share Chinese companies listed on the Shanghai and Shenzhen stock exchanges for the period from 2010 to 2015 are used. To draw inferences from the data, ordinary least squares (OLS) regression and cluster OLS are used as a baseline methodology. To control for the possible issue of endogeneity, firm-fixed-effects regression, two-stage least squares regression and propensity score matching are used.

A reliable evidence is found that tournament incentives motivate CEOs to be more socially responsible. Additional analysis reveals that the positive effect of CEO tournament incentives on corporate social responsibility performance (CSRP) is more pronounced in state-owned firms than it is in non-state-owned firms. The study’s findings are consistent with tournament theory and the conventional wisdom hypothesis, which proposes that better incentives lead to competitiveness, which improves financial and social performance.

The study’s findings have implications for companies and regulators who wish to enhance CSRP by giving tournament incentives to top managers. Investment in social responsibility may reduce the conflict between executives and employees and improve the corporate culture.

This study contributes to the existing literature by providing the first evidence that CEOs’ tournament incentives play a vital role in CSRP. The study’s findings contribute to tournament theory.

This paper aims to model the mediating effects of facilitating conditions and innovativeness in the industrial Internet of Things (IIoT) and blockchain technology (BT) on manufacturing supply chain performance (MSCP).

Partial least square structural equation modelling was used to test the goodness of the model fit and hypotheses by using SmartPLS 3.3.3. Data was collected from 464 managers in Pakistan’s automotive industry through a stratified random sampling technique.

IIoT, BT, facilitating conditions and innovativeness significantly enhanced the MSCP. Therefore, the mediation between facilitating conditions and innovativeness to IIoT and BT adoption was significant in the MSCP.

The adoption of digital technology to improve the MSCP can assist companies in reducing the cost of complex procurement, production and distribution processes through secured and efficient operations. Furthermore, organisations must establish a conducive atmosphere that fosters experimentation, collaboration and resource allocation towards technological advancements to capitalise on the advantages of these technologies effectively.

This study developed a research model integrating IIoT technology, BT, facilitating conditions and innovativeness to determine the MSCP under the resource-based view theory. The outcome of this study could help organisations design a framework to improve supply chain performance by integrating innovativeness.

The purpose of this paper is to conduct a comprehensive review of the noteworthy contributions made in the area of the Feedforward neural network (FNN) to improve its generalization performance and convergence rate (learning speed); to identify new research directions that will help researchers to design new, simple and efficient algorithms and users to implement optimal designed FNNs for solving complex problems; and to explore the wide applications of the reviewed FNN algorithms in solving real-world management, engineering and health sciences problems and demonstrate the advantages of these algorithms in enhancing decision making for practical operations.

The FNN has gained much popularity during the last three decades. Therefore, the authors have focused on algorithms proposed during the last three decades. The selected databases were searched with popular keywords: “generalization performance,” “learning rate,” “overfitting” and “fixed and cascade architecture.” Combinations of the keywords were also used to get more relevant results. Duplicated articles in the databases, non-English language, and matched keywords but out of scope, were discarded.

The authors studied a total of 80 articles and classified them into six categories according to the nature of the algorithms proposed in these articles which aimed at improving the generalization performance and convergence rate of FNNs. To review and discuss all the six categories would result in the paper being too long. Therefore, the authors further divided the six categories into two parts (i.e. Part I and Part II). The current paper, Part I, investigates two categories that focus on learning algorithms (i.e. gradient learning algorithms for network training and gradient-free learning algorithms). Furthermore, the remaining four categories which mainly explore optimization techniques are reviewed in Part II (i.e. optimization algorithms for learning rate, bias and variance (underfitting and overfitting) minimization algorithms, constructive topology neural networks and metaheuristic search algorithms). For the sake of simplicity, the paper entitled “Machine learning facilitated business intelligence (Part II): Neural networks optimization techniques and applications” is referred to as Part II. This results in a division of 80 articles into 38 and 42 for Part I and Part II, respectively. After discussing the FNN algorithms with their technical merits and limitations, along with real-world management, engineering and health sciences applications for each individual category, the authors suggest seven (three in Part I and other four in Part II) new future directions which can contribute to strengthening the literature.

The FNN contributions are numerous and cannot be covered in a single study. The authors remain focused on learning algorithms and optimization techniques, along with their application to real-world problems, proposing to improve the generalization performance and convergence rate of FNNs with the characteristics of computing optimal hyperparameters, connection weights, hidden units, selecting an appropriate network architecture rather than trial and error approaches and avoiding overfitting.

This study will help researchers and practitioners to deeply understand the existing algorithms merits of FNNs with limitations, research gaps, application areas and changes in research studies in the last three decades. Moreover, the user, after having in-depth knowledge by understanding the applications of algorithms in the real world, may apply appropriate FNN algorithms to get optimal results in the shortest possible time, with less effort, for their specific application area problems.

The existing literature surveys are limited in scope due to comparative study of the algorithms, studying algorithms application areas and focusing on specific techniques. This implies that the existing surveys are focused on studying some specific algorithms or their applications (e.g. pruning algorithms, constructive algorithms, etc.). In this work, the authors propose a comprehensive review of different categories, along with their real-world applications, that may affect FNN generalization performance and convergence rate. This makes the classification scheme novel and significant.

Given the importance of environmental protection and the crucial role of manufacturing firms in environmental degradation, the purpose of this research is to investigate the impact of green intellectual capital (GIC) on firms' green performance (GP), mediating effects of ambidextrous green innovation (GI) and moderating role of technological turbulence (TT).

The study employed a quantitative research approach with the partial least square structural equation modeling (PLS-SEM) methodology to assess the proposed relationships among the constructs on a sample of 334 executives from 134 medium and large-sized manufacturing firms.

The findings show that GIC significantly impacts different aspects of GP, including green management, green process and green product performance. Moreover, exploitative and exploratory GI serves as mediators between GIC and firms' GP. Finally, the findings demonstrate that TT moderation enhanced the effects of GIC on exploratory GI, while decreasing the effects of GIC on exploitative GI.

The research offers valuable insights and a novel strategy for manufacturing firms and policymakers to mitigate environmental degradation and attain sustainable GP by stimulating ambidextrous GI through green intangible resources.

This research adds to the current GIC, GI and GP literature by focusing on green environmental issues using the resource-based view (RBV) theory. This research also provides a significant theoretical and practical justification for explaining the relationships by differentiating ambidextrous GI between exploitative and exploratory GI's mediating effects and TT's moderating effects.

Acceptance and use of mobile shopping as the preferred shopping medium is becoming the new normal today. The proliferation of mobile shopping practices follows unsteady growth patterns in different countries. Despite challenges of price, quality and privacy matters, young consumers still lead the race to engage in mobile shopping activity in developing countries. This research investigates the determinants that either support or hinder the mobile shopping intentions of aspirant young consumers in Pakistan.

The present research applies a consumer-centric approach to the technology adoption framework to unearth the behavioral patterns of these young consumers in Pakistan. Employing the structural equation modeling technique, this research examines the significant effect of structural assurance, perceived risk, trust and various unified theory of acceptance and use of technology (UTAUT) model constructs on behavioral intention to engage in mobile shopping.

This research examines the significant effect of structural assurance, perceived risk, trust and various UTAUT model constructs on behavioral intention to engage in mobile shopping. Results also demonstrate a significant moderating effect of structural assurance and prior shopping experience on the relationship between perceived risk, trust and mobile shopping intentions. Further, the mobile shopping patterns for the male and female segment indicate a significant difference for perceived risk, trust structural assurance and social influence. The research contributes to the growing body of knowledge which advocates the application of consumer-centric customized model approach to explore various factors that either facilitate or impede the adoption of mobile shopping in a developing economy.

The study validates the need to enforce structural assurance mechanism for facilitating mobile shopping in a developing country. It also offers practical implications for online businesses and marketers striving to attract and retain more mobile customers.

The study offers practical implications for online businesses and marketers striving to attract and retain more mobile customers.

This study offers fresh insights about driving elements and impediments of mobile shopping behavioral intentions. Structural assurance and prior shopping experience appear to influence the mobile shopping behavior through direct and indirect effect.

As large multinational firms are increasingly tasked with developing sustainable supply chains, their role in improving the sustainability performance of their suppliers is critical. This paper examines the dual role of a buyer firm, as a customer and as an important stakeholder, and identifies several attributes of the buyer firm and the dyadic relationship that could help improve the sustainability performance of suppliers.

A dyadic multi-year dataset is created using financial and customer data from the Compustat database and sustainability data from MSCI ESG ratings database. The hypotheses are tested using econometric panel data techniques.

The findings indicate that a buyer's legitimacy is a key factor that affects supplier's sustainability performance. The effect of legitimacy is much higher when the buyer and supplier firms have an aligned focus on similar sustainability dimensions. The market power of the buyer also increases the effect of legitimacy, though power without legitimacy is not effective.

The study expands the understanding of how buyer firms can influence suppliers on sustainability by highlighting the key role played by legitimacy and aligned focus and the supporting role of market power. The study contributes to both the stakeholder salience literature and the buyer–supplier relationship literature by showing evidence for complementarity between market power and legitimacy. Buyer firms can use the results of the study to focus their efforts on suppliers where a significant improvement in sustainability can be expected.