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Software developers extensively use stack overflow (SO) for knowledge sharing on software development. Thus, software engineering researchers have started mining the structured/unstructured data present in certain software repositories including the Q&A software developer community SO, with the aim to improve software development. The purpose of this paper is show that how academics/practitioners can get benefit from the valuable user-generated content shared on various online social networks, specifically from Q&A community SO for software development.

A comprehensive literature review was conducted and 166 research papers on SO were categorized about software development from the inception of SO till June 2016.

Most of the studies revolve around a limited number of software development tasks; approximately 70 percent of the papers used millions of posts data, applied basic machine learning methods, and conducted investigations semi-automatically and quantitative studies. Thus, future research should focus on the overcoming existing identified challenges and gaps.

The work on SO is classified into two main categories; “SO design and usage” and “SO content applications.” These categories not only give insights to Q&A forum providers about the shortcomings in design and usage of such forums but also provide ways to overcome them in future. It also enables software developers to exploit such forums for the identified under-utilized tasks of software development.

The study is the first of its kind to explore the work on SO about software development and makes an original contribution by presenting a comprehensive review, design/usage shortcomings of Q&A sites, and future research challenges.

Considering the limitations of supply chain collaboration (SCC) literature, the purpose of this paper is to develop SCC framework and analyze the SCC practice based on the framework. The framework incorporating internal and external knowledge sharing under a collaborative culture (CC) and problem-solving environment preceded by preparedness is required.

To achieve successful collaboration, this paper encompasses problem-solving and performance measurement, preparedness, culture, relationship strength (RS) and gives resource sharing and planning as internal and external focused perspectives. Exploratory methods are used to analyze the data from industries.

CC, RS and preparedness are crucial that reflect the health of collaboration. Three levels of collaboration practice – good, moderate and weak – are prominent where the extent of SCC practice seems weak. Collaborative activities that matter more are identified. Market-based knowledge sharing is important for good and moderate SCC, while weaker collaboration does not focus on it. Interestingly, this paper finds an increasing level of collaboration may not always result in increased performance. Firms from the pharmaceutical, automobile and electrical/electronic industry tended to practice higher collaboration as compared to other industries.

By integrating market-driven management, resource-based view, and contingency theory, the SCC framework gives a new perspective. Joint planning and resource sharing are categorized as internal and external focused functional areas. The paper identifies three profiles of collaboration and discusses the importance of SCC activities in achieving performance.

The dynamic measure of risk problem in a incomplete market is discussed when stock appreciation rates are uncertain. Meanwhile, a related stochastic game problem is studied. The value of a stochastic optimal control is regarded as a reasonable measure of the risk. The form of the optimal objective is obtained by employing the tools of BSDE theory.

1. Explore the important role of sole actual controller in the innovation decision of the firm and the different effects of the ownership of sole actual controller on innovation; 2. Explore whether the role played by sole actual controllers varies in different types of firms; 3. Explore the important role of cooperative culture in the internal governance of firms and whether sole actual controller firms feel a rejection effect on cooperative culture.

The authors collect data on Shanghai and Shenzhen A-share listed companies from 2011 to 2021 to analyze the role of the sole actual controller on innovation investment, as well as the moderating effect of cooperative culture in corporate annual reports using natural language processing.

The authors find that sole actual controllers promote corporate innovation investment and that concentrated equity inhibits corporate innovation investment, while dispersed equity concentration promotes it. In addition, cooperative culture has a nonlinear moderating effect on the relationship between SACs and innovation.

On the one hand, this study focuses chiefly on the decision-making behavior of top managers, such as the SACs and shareholders, and does not account for the role of bottom-level employees or professional R&D teams in innovation. On the other hand, although this study discusses the moderating role of corporate cooperative culture, it is limited to internal cooperative culture; cooperative culture should also consider external cooperation, such as cooperation between companies or between companies and universities.

First, companies should actively implement the SAC model and scientifically select a truly compassionate and visionary SAC as the dominant person in the company. Second, the Chinese government needs to standardize the identification of actual controllers, who should not be a shareholder of the company. Third, policymakers should promote the reform of the mixed system of enterprises, optimize the shareholding structure of firms, make executives an important part of corporate governance. Fourth, cooperation culture is a good start, though firms should avoid letting it become a “double-edged sword” of the management mode of the SAC.

First, existing studies do not address the impact of SACs on innovation from the perspective of SACs, who have most influence the firm's decision-making. Focusing on the SAC's decision-making style has sufficient practical implications for future corporate innovation planning. This study used the natural language processing (NLP) module in ChatGPT to analyze the culture of cooperation in corporate annual reports. Currently, corporate culture is an obstacle to the study of corporate governance because of its obscurity and difficulty of quantification. The authors adopted a PSM (propensity score matching) approach to eliminate the endogeneity of the data, which makes the results more scientific.

This study aims to synthesize and analyze research on the Supply Chain Management Practices (SCMPs)-performance nexus, examine current knowledge, identify emerging trends, and provide plausible suggestions for future research engagements in the manufacturing sector in the context of Developing and Emerging Economies (DEEs).

Following a systematic review approach, this study analyzed 20 peer-reviewed scientific journal articles published between 2007 and 2021. The study sample was systematically selected from the Web of Science (WoS) and Google Scholar databases, following strict evaluation and selection criteria.

Numerous dimensions of SCMPs have been considered in the extant literature; however, six have stood out as the most common. In addition, operational performance stood out as the most widely investigated measure in the SCM literature. Moreover, SCMPs have predominantly shown positive effects on performance outcomes. Methodological issues that future studies should consider are suggested.

The sample size was not sufficiently large relative to the rule of thumb set in the literature because of the scarcity of studies in the manufacturing sector in the DEEs context. Despite these limitations, the results of this study provide crucial insights into knowledge and practice.

This review is the first of its kind to examine the SCMPs-performance nexus in the context of DEEs. Based on the findings of this study, future research directions are proposed.

Supply chain risks and disruptions pose a significant threat to the healthcare industry. This paper aims to synthesize the research streams in the intersection of healthcare supply chain management and risk management to identify the research gaps and future research directions.

We collected 205 papers published between 2006 and 2023 for the bibliometric analysis for the keyword co-occurrence and co-citation analysis, generating backward- and forward-looking perspectives on the scholarship in healthcare supply chain risk management (HSCRM).

This study finds a growing scholarly interest in HSCRM. Using bibliometric tools and mapping, this study presents the overall research trends in HSCRM literature and identifies seven research, namely, clusters, cost analysis, allocation, performance management, patient safety, quality, risk assessment and logistics and four research themes, namely, resilience, risk management strategy, healthcare supply chain disruption and data analytics, through the keyword co-occurrence and co-citation analyses. A future research agenda is provided based on these clusters for further investigation in this field.

This study conducted bibliometric analysis to identify clusters and associated themes for insights for further research. This approach helps advance the scholarship and proactively apply the implications in practice beyond the reactive strategy to risk management in healthcare supply chain management.

This paper aims to investigate the influence of structure parameters on giant-magnetoimpedance (GMI) effect measured by non-contact method.

The GMI sensor contains a Co-based internal magnetic core fabricated by laser cutting and an external solenoid. The influences of magnetic permeability of magnetic core and structure parameters on GMI effect were calculated in theoretical model. The output impedance, resistance, reactance and GMI ratio were measured by non-contact method using impedance analyzer.

Enhancing external magnetic field intensity can decrease the magnetic permeability of core, which has vital influences on the magnetic property and the output response of GMI sensor. In addition, increasing the width of magnetic core and the number of solenoid turns can increase the maximum GMI ratio. The maximum GMI ratio is 3,230% with core width of 6 mm and solenoid turns of 200.

Comparing with traditional contact-measured GMI sensor, the maximum GMI ratio and the magnetic field sensitivity are improved and the power consumption is decreased in non-contact measured GMI sensor. GMI sensor measured by non-contact method has a wide range of potential applications in ultra-sensitive magnetic field detection.

This paper aims to investigate magnetic field anneal in micro-patterned Co-based amorphous ribbon on giant magneto-impedance (GMI) effect enhancement.

The amorphous ribbons were annealed in transverse and longitudinal magnetic field. The influence of different field annealing directions on GMI effect and impedance Z, resistance R and reactance X with a series of line width have been deeply analyzed.

In comparison with GMI sensors microfabricated by unannealed and transversal field annealed ribbons, GMI sensor which was designed and microfabricated by longitudinal field anneal ribbon performs better. The results can be explained by the domain wall motion and domain rotation during annealing process and the geometric structure of Co-based GMI sensor. In addition, shrinking the line width of GMI sensor can promote GMI effect significantly because of the effect of demagnetizing field, and the optimum GMI ratio is 209.7 per cent in longitudinal field annealed GMI sensor with 200 μm line width.

In conclusion, annealing in longitudinal magnetic field and decreasing line width can enhance GMI effect in micro-patterned Co-based amorphous ribbon.

In the current literature, there is little systematic research on the relationship among adjustment of the income distribution, change in economic structure and improvement of macroeconomic efficiency.

This paper expands Marx's reproduction schema into the “Marx–Sraffa” three-department structure table comprising fixed capital, general means of production and means of consumption and employs China's input–output table from 1987 to 2015 to portray the relationship between income distribution and macroeconomic efficiency under investment-driven growth.

This paper calculates the wage–profit curve of China's economy and evaluates the space of macroeconomic efficiency improvement in China based on the deviation between actual and potential income distribution structure.

The results show that there is a downward trend of the profit rate, which meets Marx's theoretical prediction, and the decline in the profit rate is mainly attributed to an increase in the organic composition of capital arising from the rapid growth of fixed capital investment under extended growth. The analysis of macroeconomic efficiency shows that the space for improving macroeconomic efficiency is extremely limited under traditional growth pattern and that China must transform its economic development pattern and foster new economic growth drivers.

As a typical creative behavior, creative process engagement (CPE) has received increased attention in recent years. Leadership behaviors such as leader–member exchange (LMX) and leader creativity expectations (LCE) have been found as two key predictive factors of CPE. However, the mechanism underlying this relationship is not well understood. This study aims to clarify how LMX influences follower CPE by considering the interplay among LCE, decision autonomy and task interdependence from an interactionist perspective.

Using a sample of 371 leader–employee dyads from eight enterprises in mainland China, this study conducts a hierarchical regression analysis to test the hypotheses for the proposed model.

Results reveal that the significant two- and three-way interactions where LCE, decision autonomy and task interdependence moderate the relationship between LMX and follower CPE. The relationship between LMX and follower CPE is not significant as expected, but the moderating role of LCE is positive and significant, and the relationship is strongest when conducted with either low task interdependence or high decision autonomy.

Different from previous research that only investigated one certain leadership factor’ effect on employees' innovative behaviors, this study comprehensively considered the combined influence of two related but significantly different connotation leadership factors on follower CPE and found the contingency effect of LCE on the relationship between LMX and follower CPE. Furthermore, the authors found the regional effectiveness of the leadership factor. The effect of leadership factors on follower CPE varies under the influence of different job characteristics, and is conducive to enrich the interactionist view on follower CPE.