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Technological developments have made it possible for organizations to use enterprise resource planning (ERP) services without indulging in heavy investments like IT infrastructure, trained manpower for implementation and maintenance and updating the systems regularly to maintain business competitiveness. Plug and play model offered by cloud ERP has led to a constant creation of large data sets which are structured, semi-structured and unstructured by nature. Thus, there has been a need to analyze such complex data sets and the purpose of this paper is to focus on how cloud ERP and big data predictive analytics (BDPA) will impact the performance of a firm.

A dynamic capability view (DCV) theory-based model was developed and the authors have collected data by using an online questionnaire from India. Thereafter, the authors have analyzed it by employing structural equation modeling.

SEM analysis of 231 respondents showcases that the use of DCV theory to define the relationships of cloud ERP and BDPA has been the right move. Out of the 13 hypotheses empirically tested, only 7 hypotheses were supported by the data.

The study showcases cross-sectional data from India. It would be interesting for this study to see if the country-level differences would influence these relationships between cloud ERP and financial performance, BDPA and financial performance and cloud ERP and BDPA.

This study empirically tests the relationship of cloud ERP and BDPA through a model based on DCV theory.

This paper aims to explore the influence of marketing investment on drug diffusion processes, to analyze the heterogeneity of the diffusion characteristics and to understand the drug diffusion patterns in the prescription and over-the-counter (OTC) markets.

The study introduces marketing investment into the Bass model. The authors use the Generalized Bass Model (GBM) to examine the influence of marketing efforts on drug diffusion in Chinese prescription and OTC markets.

The results of this study suggest that the imitation effect in the prescription drug market is greater than that in the OTC drug market; drug diffusion in the OTC market reaches saturation earlier in the diffusion process. Before reaching the critical state, the effect of marketing investment on drug diffusion in the OTC market is greater than that in the prescription market, and after the critical state, drug diffusion in the prescription market is more sensitive to marketing investment.

The study demonstrates the value of the GBM in empirical analyses of drug diffusion across two distinct markets, and the marketing regulation policies governments adopt have a powerful impact on the speed at which drugs become available in different markets. It enriches the extant product diffusion literature by highlighting the different diffusion patterns of the two segments of pharmaceutical market.

The aim of this paper is to study reverse logistics network design in order to better facilitate the location of factories, online retailers, and the third party logistics in the context of e‐commerce.

Drawing on types of third party collections of returned products, the paper proposes a 0‐1 mixed integrate linear programming (0‐1MILP) mathematic model for reverse logistics networks in e‐business and a further mathematical model is discussed in relation to determining the market demands and returns. Furthermore, a case study is developed and described with the intention of illustrating the value of this model and network.

The paper identifies possibilities for the application of the reverse logistics network models to deal with returned products from customers in companies using e‐business.

There is scope for future research to build on the present research and consider further factors in relation to the influences on return logistics.

This paper provides novel insights for e‐companies setting up and operating a reverse logistics network. The application of these models could decrease costs and allow optimal decisions on price and return price in order to increase efficiency and profit levels.

This paper aims to examine the double-edged sword effects of work-related rumination on employees’ innovative performance. Drawing upon Conservation of Resources (COR) theory, this study developed a model to reveal the mechanism through which work-related rumination affects employees’ innovative performance.

Data were collected from a sample of employees and their managers at an information technology services firm in China. A two-wave data collection method with a one-month interval was employed. The analysis was conducted using structural equation modeling on 482 paired manager-subordinate responses.

Our findings highlight the complex interplay between work-related rumination and innovative performance. Specifically, affective rumination was found to detract from employees’ innovative performance, whereas problem-solving pondering had a positive effect. Notably, creative self-efficacy emerged as a key mediator in these relationships. Furthermore, employees’ perceived organizational support moderated the impact of rumination on creative self-efficacy and, consequently, on innovative performance, buffering the negative effects of affective rumination and enhancing the positive effects of problem-solving pondering.

Firstly, it enriches the existing literature on work-related rumination by exploring its nuanced influence on employees’ innovative performance. Secondly, it illuminates the underlying mechanism through which work-related rumination affects innovative performance, mediated by creative self-efficacy. Lastly, it highlights the crucial role of perceived organizational support in moderating these relationships, offering valuable insights for practitioners seeking to foster a more innovative work environment.

This research aims to comprehensively investigate when and how cognitive conflict benefits team innovation in cross-functional project teams (CFPTs), by exploring the moderating role of knowledge leadership and dual mediation mechanisms of elaboration of task-related information/knowledge and affective conflict.

All hypotheses have been empirically tested by using structural equation model to analyze the quantitative data from a questionnaire survey covering 73 CFPTs in China.

Results indicate that knowledge leadership positively moderates the relationship between cognitive conflict and CFPT innovation. This moderating effect is directly or indirectly revealed by the dual mediating roles of task-related information/knowledge elaboration and affective conflict, which are two processes manifesting whether cognitive conflict can or cannot be incorporated into team innovation.

Despite the external validity of results limited by convenient sampling method, the findings offer implications for promoting CFPT innovation. This can be achieved by developing competent knowledge leadership into team sensegiver, dissent reconciler and facilitator to accentuate benefits of cognitive conflict in information/knowledge elaboration and attenuate the likelihood of escalating to affective conflict.

This study advances the understanding of why cognitive conflict has an equivocal effect on team innovation in the context of CFPT by originally revealing how leaders’ role in information/knowledge management acts as a contingency and suggesting the dual mediating mechanisms that reflect the contingent impact. Project-based teams or organizations, characterized by cognitive clashes, can enhance innovation performance by shaping the meaningfulness of information/knowledge activities triggered by cognitive conflict.

Enterprises use social media for their daily work. The use of social media in the workplace is crucial for social connections, the growth and evolution of the enterprise, and it opens up new avenues for voice behavior. Employee voice involves the expression of ideas or opinions towards enterprise and is beneficial for employee work and enterprise development. Extant studies of voice behavior usually focus on the leadership and employee factors. However, the internal mechanism of voice behavior, especially the interrelationship between different kinds of social media use and voice behavior has not been well investigated. To fill that research gap, this study analyzes the internal mechanism of voice behavior, taking the effects of social media use and social capital into consideration.

Using structural equation model, this study collected data from employees using social media and analyzed the data using the software of Smartpls 3.0, SPSS and AMOS, in order to analyze the internal mechanism of voice behavior among employees.

Based on social capital theory, this study investigates the relationship between social media use, social capital and voice behavior, and provides some insights into the mechanism of voice behavior. The social media use, social capital and voice behavior are divided into several kinds in order to clarify the internal mechanism of voice behavior more comprehensively. The empirical results show that: (1) Social media use for both work and social-related purposes could positively affect employees’ promotive and prohibitive voice behaviors. (2) Social capital mediates the relationship between social media use and voice behavior. (3) In the process of social media use influencing employees’ voice behavior, employees of different genders and ages show significant differences in social capital and voice behavior.

This study explored the internal mechanism of voice behavior, which could help to elicit the relationship between social media use and voice behavior. By integrating the roles of social capital, individual differences, this study could uncover the deep internal mechanism of employee voice behavior more comprehensively, broadening social capital theory and enriching the researches of voice behavior among employees.

The paper seeks to investigate the effects of psychological contract on control mechanisms in outsourced ISD projects, based on control theories and psychological contract theories.

The paper is a multiple case study involving five outsourced projects completed by one of the largest and most successful telecommunication vendors in China. The company was the client in three of the projects and the vendor in the other two.

Based on first‐hand observations by the first author over a two‐year period and follow‐up interviews, four scenarios of match and mismatch of psychological contract between the client and vendor are identified, labeled as mutual transaction, client vulnerable, vendor vulnerable, and mutual loyalty. Moreover, the effect of psychological contract in shaping organizational control and outsourcing outcomes in the four different scenarios is revealed. For example, mutual transaction was associated with an emphasis on outcome control by the client. In contrast, mutual loyalty was associated with more informal control (self‐control and clan control). Furthermore, in the cases of mismatch between the client's and vendor's psychological relationship, the client implemented more behavior control and encouraged self‐control by its partner.

This research is, to the best of the author's knowledge, one of the first attempts to bring together psychological contract theory and organizational control theory in the domain of IT offshore outsourcing research. It reveals the effect of psychological contract in shaping organizational control in the four different scenarios labeled as mutual transaction, client vulnerable, vendor vulnerable, and mutual loyalty.

This paper aims to study the impact of external fairness of executive compensation on M&A premium, and examine the moderate role of institutional investors. The high M&A premium is the main factors that induce the huge impairment of listed companies’ goodwill and the plummeting performance. Executives are the decision-makers of M&As, and their decision-making process is inevitably affected by the psychological factors. In recent years, institutional investors have become an important external force that can affect the governance of listed companies.

The authors use M&A data of listed companies from 2008 to 2018 and use OLS regression to test the relationship between executive compensation fairness and M&A premium.

The results show that the lower the external fairness of executive compensation, the greater the M&A premium. Institutional investors can effectively reduce the impact of external compensation unfairness on M&A premiums. The mechanism tests show that executives' psychological perception of fairness induced by external unfairness reduces their motivation to work and prompts them to use high premium to seek alternative compensation incentives. Further examinations of executive characteristics and corporate characteristics show that the role of external unfairness in executive compensation in driving M&A premiums is more pronounced in companies with longer executive tenure, weaker executive reputation incentives and private property.

This paper enriches the research on the pre-factors of M&A premiums from the perspective of executives’ psychological perception of fairness, provides evidence that institutional investors play a positive governance role and provides decision-making references for companies to take corresponding measures to reduce M&A premium risks.

This paper aims to effectively achieve endmembers and relative abundances simultaneously in hyperspectral image unmixing yield. Hyperspectral unmixing, which is an important step before image classification and recognition, is a challenging issue because of the limited resolution of image sensors and the complex diversity of nature. Unmixing can be performed using different methods, such as blind source separation and semi-supervised spectral unmixing. However, these methods have disadvantages such as inaccurate results or the need for the spectral library to be known a priori.

This paper proposes a novel method for hyperspectral unmixing called fuzzy c-means unmixing, which achieves endmembers and relative abundance through repeated iteration analysis at the same time.

Experimental results demonstrate that the proposed method can effectively implement hyperspectral unmixing with high accuracy.

The proposed method present an effective framework for the challenging field of hyperspectral image unmixing.

This study aims to help businesses cope with consumers' no-show behaviour from a multistage perspective. It specifically identifies no-show reasons at each stage of appointment services and proposes the corresponding coping strategies.

By focusing on an outpatient appointment service, we interviewed 921 no-show patients to extract no-show reasons, invited 18 hospital managers to propose coping strategies for these reasons using a Delphi method and evaluated the proposed strategies based on EDAS (Evaluation based on Distance from Average Solution).

The results reveal ten reasons for no-show behaviour (i.e. system service quality, overuse, did not know the appointment, self-judgment, forget, waiting time, lateness, uncontrollable problems, time conflict and service coordination), which have nine coping strategy themes (i.e. prepayment, system intelligence, target, subjective norm, system integration, ease of navigation, reminder, confirmation and cancellation). We classify the ten reasons and nine themes into scheduling, waiting and execution stages of an appointment service.

This study provides a package of coping strategies for no-show behaviour to deal with no-show reasons at each appointment service stage. It also extends the research in pre-service management through appointment services.