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A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

This study aims to explore the impact of ecosystem-related digital decoupling capability (DDC) and digital integrative capability (DIC) on manufacturing firms’ radical service innovation (RSI) and the moderating effect of strategic flexibility, specifically resource flexibility (RF) and culture flexibility (CF).

This study employed empirical survey data collected from 238 Chinese manufacturing firms to test all hypotheses through hierarchical multiple regression analyses.

DDC and DIC have positive effects on RSI, with DDC exerting a stronger impact. RF and CF strengthen the positive effect of DIC on RSI, whereas CF diminishes DDC’s positive effect on RSI, and RF does not moderate this effect.

Manufacturing firms should prioritize developing ecosystem-related DDC and DIC to drive RSI, especially DDC. Managers should improve firms’ RF and CF when leveraging DIC to drive RSI. However, they should minimize the negative impact of CF when leveraging DDC to drive RSI.

This study shifts the service innovation capabilities from the firm to the ecosystem level, opening a new perspective for exploring RSI’s driving mechanism. With RF and CF as the moderators, the findings reveal the contingent impact mechanism of ecosystem-related digital capabilities on RSI, which provides profound insights into the complex role of strategic flexibility in the new contexts.

Despite a growing number of manufacturing firms actively collaborating with ecosystem members aiming for advanced service solutions, it remains unclear how digital collaboration capability (DCC) affects incremental service innovation (ISI) and radical service innovation (RSI) in the context of ecosystems. Drawing on dynamic capabilities theory and resource orchestration theory, this study aims to investigate the impacts of DCC on ISI/RSI and examine the mediating role of organizational agility (OA).

In this empirical paper, the authors obtained questionnaire data from 238 Chinese manufacturing firms embedded in the ecosystems. Then, the authors examined all the hypotheses through hierarchical regression analyses.

The empirical evidence indicates that DCC has a distinct effect on ISI and RSI. DCC positively affects ISI, whereas DCC shows an inverted U-shaped effect on RSI. In addition, OA mediates the positive effect of DCC on ISI within a certain range, whereas OA always mediates the inverted U-shaped effect of DCC on RSI.

This study enriches and extends existing research on DCC and service innovation by elucidating the heterogeneous effects of DCC on ISI/RSI and the complicated mediating role of OA. This study also has practical implications for manufacturing firms to revisit their collaboration capability and agility to boost ISI/RSI in the context of ecosystems.

This study aims to examine the potential of Information Ethics (IE) to serve as a coherent ethical foundation for the library and information science profession (LIS profession).

This study consists of two parts: the first part present IE’s central theses and the main critiques it has received; the second part offers the authors' own evaluation of the theory from the LIS perspective in two steps: (1) assessing its internal consistency by testing its major theses against each other; (2) assessing its utility for resolving frequently debated LIS ethical dilemmas by comparing its solutions with solutions from other ethical theories.

This study finds that IE, consisting of an informational ontology, a fundamental ethical assertion and a series of moral laws, forms a coherent ethical framework and holds promising potential to serve as a theoretical foundation for LIS ethical issues; its inclusion of nonhuman objects as moral patients and its levels of abstraction mechanism proved to be particularly relevant for the LIS profession. This study also shows that, to become more solid an ethical theory, IE needs to resolve some of its internal contradictions and ambiguities, particularly its conceptual conflations between internal correctness, rightness and goodness; between destruction, entropy and evil; and the discrepancy between its deontological ethical assertion and its utilitarian moral laws.

This study alerts LIS professionals to the possibility of having a coherent ethical foundation and the potential of IE in this regard.

This study provides a systemic explication, evaluation and field test of IE from the LIS perspective.

The purpose of this systematic literature review (SLR) is to examine the theoretical landscape of knowledge hiding (KH) research, identifies prevailing theories, the different ways KH is understood within these theories and the underlying assumptions that shape these views. Based on this, ideas for further research are derived to advance the theoretical basis of KH studies.

Using a theory-based SLR, the authors analysed 170 scientific papers from Scopus and Web of Science. This involved thematic analysis to categorise theories frequently applied in KH research and a detailed examination to link core assumptions to these theoretical perspectives.

The analysis revealed a reliance on 86 distinct theories, with a notable emphasis on social exchange theory and conservation of resources theory. KH is predominantly conceptualised as a negative, objective, reactive and relational behaviour rooted in social reciprocity and resource conservation. The review uncovers the multifaceted nature of KH, challenging the field to incorporate broader theoretical views that encompass positive aspects, subjective experiences, strategic intentions and non-relational determinants of KH.

To the best of the authors’ knowledge, this is the first study to systematically map and analyse the theoretical underpinnings of KH research. It offers a unique contribution by categorising the diverse theories applied in KH studies and explicitly linking these theories to their inherent assumptions about KH. This approach provides a comprehensive overview that not only identifies gaps in the current research landscape but also proposes alternative theoretical perspectives for exploring KH, thereby setting a new direction for future studies in this field.

Motivated by the real-world practice of the thriving e-commerce, manufacturers are transcending traditional boundaries of merely producing and selling directly by implementing encroachment. Concurrently, supply chain (SC) members who overlook the corporate social responsibility (CSR) sharing will be left behind, which is closely linked to their profits. This paper aims to investigate a better way to share CSR under the scenarios of manufacturer encroachment and no-encroachment.

This paper constructs game-theoretic models in a SC consisting of a manufacturer (M) and a retailer (R), where the manufacturer can sell products by retailing, and may sell directly by implicating encroachment. The manufacturer and retailer jointly consider whether to share CSR and the proportion of it by taking consumer surplus into account. Furthermore, equilibriums for each model are derived using backward induction. Then, the authors analyse the impact of CSR sharing proportion and compare the equilibrium outcomes under different scenarios. Finally, the numerical analyses are presented to verify the results.

Several interesting results are found in this paper. First, the retailer shares more CSR can benefit SC members and social welfare when the manufacturer does not implement encroachment. However, the results may change which is decided by the unit cost of encroachment when the manufacturer does so. Second, the proportion of CSR shared by manufacturer and the unit cost of encroachment has an interactive impact on equilibrium outcomes. Finally, both manufacturer encroachment and SC members share CSR may be the best for the perspective of SC members and consumers.

Based on the analytical results, this paper provides novel managerial implications to assist manufacturer and retailer in determining the optimal strategies for CSR sharing and encroachment. Furthermore, the appropriate proportion of CSR shared by manufacturer and the unit cost of encroachment may let manufacturer, retailer and consumer surplus achieve a win-win-win situation.

To the best of the authors’ knowledge, this paper is the first attempt to explore the strategy of CSR sharing under the scenarios of manufacturer encroachment and no-encroachment.

Since the idea of “Unethical Pro-organisational Behaviour” (UPB) was introduced in 2010, a substantial corpus of empirical research has contributed to its expanding, contemporary knowledge. This includes research studies on how leadership exerts an influence on UPB. This paper aims to consolidate the current understanding of organisational leadership’s impact on employee UPB and offer future research agendas.

A systematic literature review (SLR) using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines was adopted for the study. Literature that satisfied the search conditions was examined. The factors determining leadership’s influence on UPB were studied, and the findings were thematically synthesised.

Leader behaviour plays a large part in influencing UPB in organisations. Leader-member exchange and organisational belonging create favourable circumstances for UPB in organisations. UPB is moderated by the employee’s personal moral orientation.

UPB is unethical behaviour that benefits the organisation and is likely to be rewarded. However, there is a cost that other stakeholders pay. UPB has been researched since 2010, as well as the role of leaders in perpetuating UPB. However, there has not been an SLR of this study. This paper seeks to capture the essence of the research so far and pave a path for future research on the subject. These insights would prove valuable to management practitioners and academic experts.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.

Introduction: When people need to take decisions, being economic decisions or otherwise, their decisions tend to rely on information the brain has already processed, and this includes the resources that the person has already invested. This is called sunk cost bias in the behavioural economics literature. On the other hand, mental practices could lead to the mental accounting bias, where people allocate a different value to a fixed amount of money, depending on circumstances.

Purpose: In this chapter, both biases mental accounting and sunk cost are investigated for the tourism industry in Turkey.

Methodology: The topic is researched through scenario-based questions and the Chi-square Automatic Interaction Detector (CHAID) method is applied.

Findings: As a result, it could be reported that people, regardless of gender, fall into sunk cost and mental accounting biases in decisions relating to their vacations. Mental accounting biases can be primarily explained using the scenario questions posed rather than gender, education, and income while sunk cost bias is explained by status, ‘being s university student’ and ‘income level’.

Practical implications: Rapid price changes in the tourism industry can disturb consumers who are mental accounting and sunk cost biased. So, they can change their holiday preferences or be dissatisfied with it and give negative feedback.

Purpose: The economies of the European Union (EU) countries are significantly affected by new developments in technology and digital transformations, requiring tailored policies to bridge gaps and boost economic development. This chapter analyses the impact of the digital economy in EU countries according to the level of economic growth.

Need for study: Assessing the interaction between economic growth and digitalisation, focussing on digital transformations, digital skills, and economic growth, this chapter designs advanced theoretical and empirical research by building on certain important research issues.

Methodology: The research framework relies on assessing the correlation between the Digital Economy and Society Index (DESI) and economic growth. Based on Eurostat data, this research employs panel econometric models to uncover causal relationships between digital policies and economic growth, incorporating macroeconomic variables and country-specific digital policies. The models are designed through the panel-corrected standard errors (PCSEs) method and robust regression with Huber iteration (RRHI) to ensure unbiased and robust estimates.

Findings: Main findings include that digitalisation coordinates and digital skills are essential for improving economic development in the EU, with benefits for economic growth. These advances affect balance and overall performance and can support policymakers in strengthening their understanding of this scientific field.

Practical implications: The degree of development and the underlying technology underlying determine how the digital economy affects economic growth. Decision-makers can utilise these results to improve digital policies within the EU, favourably impacting the economic development of EU member states.