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Article
Publication date: 3 February 2025

Jianhong Zhang, Suzana B. Rodrigues, Jiangang Jiang and Chaohong Zhou

The purpose of this paper is to investigate the impact of political instability at the local level on foreign firms in China. Building on the literature on political embeddedness…

69

Abstract

Purpose

The purpose of this paper is to investigate the impact of political instability at the local level on foreign firms in China. Building on the literature on political embeddedness and business power, the authors propose a theoretical framework to explain how political turnover can affect foreign firms’ performance and how they respond to such challenges by leveraging their power bases.

Design/methodology/approach

To test the hypotheses, the authors apply fixed effects regression to an unbalanced panel data set comprising 13,360 foreign firms from 1998 to 2013 and the political replacement that involved changes in provincial governors.

Findings

The findings confirm that political turnover incidents have a negative impact on the performance of foreign firms in China. However, the authors also found that this negative relationship is weaker for firms that can choose various types of power sources. Specifically, the study reveals that foreign firms with large firm size, government ownership and a strong foreign direct investment community are better qualified to mitigate the negative effects of political instability.

Originality/value

This study contributes to the literature by developing the understanding of how political uncertainties and risks affect the performance of foreign firms in China and the importance of firms’ power in counterbalancing these effects. The research provides valuable insights into how multinational corporations can exploit their power to manage the effects of local political turnover, which has practical implications for the strategy and management of foreign firms operating in China.

Details

Multinational Business Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1525-383X

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Article
Publication date: 14 January 2025

Weilong Liu, Zhongguo Wang and Xv Zhang

This paper aims to integrate the latent semantic features of annual report text with accounting indicators to construct a financial fraud identification model, and quantitatively…

39

Abstract

Purpose

This paper aims to integrate the latent semantic features of annual report text with accounting indicators to construct a financial fraud identification model, and quantitatively analyze the impact of different corporate risks on financial fraud behavior in different industries, providing a reference for identifying financial fraud.

Design/methodology/approach

This paper obtains 3,860 corporate annual report samples and accounting indicators from 2001 to 2020 through crawlers and the CSMAR database as our experimental subjects. By integrating latent semantic features with accounting indicators and textual language features, a new indicator system group is constructed. Based on this indicator system group, multiple model identification effects are compared and a stacking-based enterprise financial fraud identification model is constructed. In addition, an econometric model is established to verify the impact of latent semantic features related to enterprises on corporate financial fraud.

Findings

The experimental results show that the constructed stacking-based enterprise financial fraud identification model performs better than other machine learning models and can effectively identify financial fraud. The econometric model established for the latent semantic information of annual reports explains the impact of different corporate trends on fraud behavior in different industries.

Originality/value

This paper combines the textual latent semantic features of annual reports with accounting indicators, expands the scope of data analysis, introduces the idea of ensemble learning, updates the financial fraud identification algorithm and constructs an econometric model for further analysis, providing a reference for financial fraud identification.

Details

Journal of Accounting & Organizational Change, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1832-5912

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Article
Publication date: 22 October 2024

Shengbin Ma, Zhongfu Li and Jingqi Zhang

The waste-to-energy (WtE) project plays a significant role in the sustainable development of urban environments. However, the inherent “Not in my backyard” (NIMBY) effect presents…

57

Abstract

Purpose

The waste-to-energy (WtE) project plays a significant role in the sustainable development of urban environments. However, the inherent “Not in my backyard” (NIMBY) effect presents substantial challenges to site selection decisions. While effective public participation is recognized as a potential solution, research on incorporating it into site selection decision-making frameworks remains limited. This paper aims to establish a multi-attribute group decision-making framework for WtE project site selection that considers public participation to enhance public satisfaction and ensure project success.

Design/methodology/approach

Firstly, based on consideration of public demand, a WtE project site selection decision indicator system was constructed from five dimensions: natural, economic, social, environmental and other supporting conditions. Next, the Combination Ordered Weighted Averaging (C-OWA) operator and game theory were applied to integrate the indicator weight preferences of experts and the public. Additionally, an interactive, dynamic decision-making mechanism was established to address the heterogeneity among decision-making groups and determine decision-maker weights. Finally, in an intuitive fuzzy environment, an “acronym in Portuguese of interactive and multi-criteria decision-making” (TODIM) method was used to aggregate decision information and evaluate the pros and cons of different options.

Findings

This study develops a four-stage multi-attribute group decision-making framework that incorporates public participation and has been successfully applied in a case study. The results demonstrate that the framework effectively handles complex decision-making scenarios involving public participation and ranks potential WtE project sites. It can promote the integration of expert and public decision-making preferences in the site selection of WtE projects to improve the effectiveness of decision-making. In addition, sensitivity and comparative analyses confirm the framework’s feasibility and scientificity.

Originality/value

This paper provides a new research perspective for the WtE project site selection decision-making, which is beneficial for public participation to play a positive role in decision-making. It also offers a valuable reference for managers seeking to effectively implement public participation mechanisms.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 26 September 2024

Umar Farooq Sahibzada, Nadia Aslam, Muhammad Muavia, Muhammad Shujahat and Piyya Muhammad Rafi-ul-Shan

The rapid evolution of digital innovation has significantly revolutionized the business landscape for entrepreneurs. Embracing digital innovation is crucial for all stakeholders…

215

Abstract

Purpose

The rapid evolution of digital innovation has significantly revolutionized the business landscape for entrepreneurs. Embracing digital innovation is crucial for all stakeholders to achieve sustainable development goals (SDGs) and promote sustainability. However, there is little understanding of how entrepreneurial leadership in developing nations has proactively responded to the challenge of digital innovation. Based on Drucker’s productivity theory, this study examines the relationship between entrepreneurial leadership (EL), digital orientation (DO) and digital capability (DC) as predictors of digital innovation (DI). The proposed model aims to establish the causal connections between variables and elucidate the complex interplay between digital innovation and the resulting outcome of sustainable performance (SP).

Design/methodology/approach

Two research studies were carried out in the Chinese IT industry to assess the efficacy of the theoretical framework among IT workers. Study 1 utilized a three-week, two-week time-lagged design (N = 299), while Study 2 used a two-week, four-week survey design (N = 341). The study used Smart-PLS 4.0 for data analysis.

Findings

The results showed that entrepreneurial leadership significantly impacts employee digital orientation and digital capabilities, fostering digital innovation. Moreover, digital innovation has a significant impact on sustainable performance.

Originality/value

The study’s findings allow authors to contribute to the existing scholarship on employee digital orientation, digital capabilities, digital innovation and sustainable performance in an emerging economy.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 25 April 2024

Mengmeng Shan and Jingyi Zhu

This paper aims to investigate the relationship between corporate environmental, social and governance (ESG) ratings and leverage manipulation and the moderating effects of…

590

Abstract

Purpose

This paper aims to investigate the relationship between corporate environmental, social and governance (ESG) ratings and leverage manipulation and the moderating effects of internal and external supervision.

Design/methodology/approach

The authors draw on a sample of Chinese non-financial A-share-listed firms from 2013 to 2020 to explore the effect of ESG ratings on leverage manipulation. Robustness and endogeneity tests confirm the validity of the regression results.

Findings

ESG ratings inhibit leverage manipulation by improving social reputation, information transparency and financing constraints. This effect is weakened by internal supervision, captured by the ratio of institutional investor ownership, and strengthened by external supervision, captured by the level of marketization. The effect is stronger in non-state-owned firms and firms in non-polluting industries. The governance dimension of ESG exhibits the strongest effect, with comprehensive environmental governance ratings and social governance ratings also suppressing leverage manipulation.

Practical implications

Firms should strive to cultivate environmental awareness, fulfil their social responsibilities and enhance internal governance, which may help to strengthen the firm’s sustainability orientation, mitigate opportunistic behaviours and ultimately contribute to high-quality firm development. The top managers of firms should exercise self-restraint and take the initiative to reduce leverage manipulation by establishing an appropriate governance structure and sustainable business operation system that incorporate environmental and social governance in addition to general governance.

Social implications

Policymakers and regulators should formulate unified guidelines with comprehensive criteria to improve the scope and quality of ESG information disclosure and provide specific guidance on ESG practice for firms. Investors should incorporate ESG ratings into their investment decision framework to lower their portfolio risk.

Originality/value

This study contributes to the literature in four ways. Firstly, to the best of the authors’ knowledge, it is among the first to show that high ESG ratings may mitigate firms’ opportunistic behaviours. Secondly, it identifies the governance factor of leverage manipulation from the perspective of firms’ subjective sustainability orientation. Thirdly, it demonstrates that the relationship between ESG ratings and leverage manipulation varies with the level of internal and external supervision. Finally, it highlights the importance of governance in guaranteeing the other two dimensions’ roles by decomposing overall ESG.

Details

Sustainability Accounting, Management and Policy Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-8021

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Article
Publication date: 3 July 2024

Qian Wang, Yan Wan, Feng Feng, Ziqing Peng and Jing Luo

Public reviews on educational robots are of great importance for the design, development and management of the most advanced robots with an educational purpose. This study…

77

Abstract

Purpose

Public reviews on educational robots are of great importance for the design, development and management of the most advanced robots with an educational purpose. This study explores the public attitudes and emotions toward educational robots through online reviews on Weibo and Twitter by using text mining methods.

Design/methodology/approach

Our study applied topic modeling to reveal latent topics about educational robots through online reviews on Weibo and Twitter. The similarities and differences in preferences for educational robots among public on different platforms were analyzed. An enhanced sentiment classification model based on three-way decision was designed to evaluate the public emotions about educational robots.

Findings

For Weibo users, positive topics tend to the characteristics, functions and globalization of educational robots. In contrast, negative topics are professional quality, social crisis and emotion experience. For Twitter users, positive topics are education curricula, social interaction and education supporting. The negative topics are teaching ability, humanistic care and emotion experience. The proposed sentiment classification model combines the advantages of deep learning and traditional machine learning, which improves the classification performance with the help of the three-way decision. The experiments show that the performance of the proposed sentiment classification model is better than other six well-known models.

Originality/value

Different from previous studies about attitudes analysis of educational robots, our study enriched this research field in the perspective of data-driven. Our findings also provide reliable insights and tools for the design, development and management of educational robots, which is of great significance for facilitating artificial intelligence in education.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 15 August 2024

Qian Chen, Yeming Gong, Yaobin Lu and Xin (Robert) Luo

The purpose of this study is twofold: first, to identify the categories of artificial intelligence (AI) chatbot service failures in frontline, and second, to examine the effect of…

1062

Abstract

Purpose

The purpose of this study is twofold: first, to identify the categories of artificial intelligence (AI) chatbot service failures in frontline, and second, to examine the effect of the intensity of AI emotion exhibited on the effectiveness of the chatbots’ autonomous service recovery process.

Design/methodology/approach

We adopt a mixed-methods research approach, starting with a qualitative research, the purpose of which is to identify specific categories of AI chatbot service failures. In the second stage, we conduct experiments to investigate the impact of AI chatbot service failures on consumers’ psychological perceptions, with a focus on the moderating influence of chatbot’s emotional expression. This sequential approach enabled us to incorporate both qualitative and quantitative aspects for a comprehensive research perspective.

Findings

The results suggest that, from the analysis of interview data, AI chatbot service failures mainly include four categories: failure to understand, failure to personalize, lack of competence, and lack of assurance. The results also reveal that AI chatbot service failures positively affect dehumanization and increase customers’ perceptions of service failure severity. However, AI chatbots can autonomously remedy service failures through moderate AI emotion. An interesting golden zone of AI’s emotional expression in chatbot service failures was discovered, indicating that extremely weak or strong intensity of AI’s emotional expression can be counterproductive.

Originality/value

This study contributes to the burgeoning AI literature by identifying four types of AI service failure, developing dehumanization theory in the context of smart services, and demonstrating the nonlinear effects of AI emotion. The findings also offer valuable insights for organizations that rely on AI chatbots in terms of designing chatbots that effectively address and remediate service failures.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

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Article
Publication date: 3 December 2024

Mengyuan Cheng, Heap-Yih Chong, Guoliang Liu and Qian Li

Perceived justice is crucial to achieving public–private partnership (PPP) projects’ goals, but little is known about the transmission mechanism of perceived justice that affects…

30

Abstract

Purpose

Perceived justice is crucial to achieving public–private partnership (PPP) projects’ goals, but little is known about the transmission mechanism of perceived justice that affects added value in PPP projects. Therefore, this research intends to investigate the link between perceived justice and PPP projects’ added value and their underlying mechanism by analysing the mediating role of cooperative behaviour.

Design/methodology/approach

Based on 246 valid survey data collected from the Chinese PPP professionals, structural equation modelling was adopted to analyse and test the proposed hypotheses.

Findings

The results show all three dimensions of perceived justice positively correlated with PPP projects’ added value. The influence effect from high to low was determined to be as follows: interactive, distributive and procedural justice. Moreover, both perfunctory and consummate performance were found to be positively correlated with and thus of great importance to PPP projects’ added value, but perfunctory performance was found to have a greater influence coefficient. The relationship between perceived justice and PPP projects’ added value is mediated by perfunctory and consummate performance. Therefore, the strategies of perceived justice in improving added value are verified in the context of Chinese PPP projects.

Research limitations/implications

The findings of this study can help realise added value in three ways. Firstly, new perspectives for PPP project added value should be proposed by combining the improvement of project basic objectives and the realisation of the participants’ implicit demands. Secondly, the effects of different perceived justice on added value should be analysed instead of a single dimension of perceived justice. Thirdly, the mediating effects of different types of cooperative behaviour that may influence the relationship between perceived justice and added value should be evaluated.

Practical implications

This study contributes to a better understanding of the relationship between perceived justice and PPP projects’ added value and provides a reliable reference for project managers to achieve added value outcomes in PPP projects. In addition, this study reveals the impact of perceived justice on PPP projects’ added value and the path of perceived justice transformation. This provides a useful reference for project managers to take advantage of the positive effects of distributive, interactive and procedural justice to enhance inter-organizational cooperative behaviour. This study thus helps improve the practice and value of PPP projects by using the right strategy of perceived justice.

Originality/value

The research clarifies the impacts of multidimensional perceived justice for added value of PPP projects throughout the implementation process. It offers a new perspective on PPP projects’ added value by combining the improvement of the realisation of participants’ implicit claims.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 8 December 2023

Qian Chen, Changqin Yin and Yeming Gong

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

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Abstract

Purpose

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Design/methodology/approach

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

Findings

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

Originality/value

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

Research highlights

  1. The study investigates customers' adoption of AI chatbots' recommendation.

  2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

  3. The central and peripheral cues are generalized according to cooperative principle theory.

  4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

  5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

  6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

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Article
Publication date: 4 December 2024

Matthew Phillip Johnson, Jakob Strobel and Gregory Trencher

To achieve net-zero by mid-century consistent with the Paris Agreement, companies must urgently formulate and implement decarbonization actions. While previous research has…

118

Abstract

Purpose

To achieve net-zero by mid-century consistent with the Paris Agreement, companies must urgently formulate and implement decarbonization actions. While previous research has categorized numerous carbon management and carbon accounting actions, these domains have often been studied in isolation. We classify carbon management actions into four categories (inaction, ineffective, supportive and effective) and connect them to carbon accounting actions in a subsequent step, revealing four archetypical patterns of corporate decarbonization responses. The primary aim of this empirical study is to comprehensively assess how companies implement carbon management and carbon accounting actions in parallel and build an understanding of the various factors affecting each other, and how these domains affect carbon performance altogether.

Design/methodology/approach

This study adopted a maximum diverse sampling approach to assess carbon management actions in 22 international companies and link them to carbon accounting actions. Data sources included interviews with sustainability managers, field notes from a joint meeting and sustainability reports. The heterogeneous sample aimed for maximum diversity, covering various sectors and headquarters locations, yet all companies have communicated a commitment to reducing carbon emissions. A qualitative content analysis was used to find connections between carbon management actions and carbon accounting actions, resulting in four archetypical patterns.

Findings

The study identifies a range of carbon management actions, from inaction to effective action, and corresponding carbon accounting actions for monitoring, disclosure, and internal information use. Effective carbon management actions correlate with comprehensive carbon accounting actions, while ineffective management shows limited use of these actions. Based on these findings, we examine links between carbon management and carbon accounting and identify four archetypical patterns of corporate decarbonization responses.

Originality/value

This study examines the interconnectedness of carbon management and carbon accounting, identifying archetypical patterns that explain their effectiveness in reducing corporate carbon emissions. It provides a framework for analyzing companies’ carbon management and highlights the essential role of carbon accounting in monitoring, disclosing and internal data use. Said framework and conclusions can guide future research and management.

Details

Accounting, Auditing & Accountability Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0951-3574

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