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Economic policy uncertainty has increased around the world since the financial crisis of 2007–2008. While scholars have devoted a lot of time and energy to investigating the impact of economic policy uncertainty (EPU) on firm innovation, they have not reached consistent research conclusions. This study aimed to clarify the above research differences by exploring the impact of EPU on firms' relative exploitative innovation emphasis, so as to provide a more comprehensive and granular understanding of the relationship between EPU and firm innovation.

This study obtained 17,165 firm-year data points from 3,107 listed companies in China. It analyzed the above data with a fixed effects model. In addition, this study used an instrumental variables method to solve potential endogeneity problems.

Based on real options theory and contingency theory, the authors proposed and found that EPU has a significant positive effect on relative exploitative innovation emphasis. In addition, the authors proposed and found that this effect is more pronounced in industries with high technological uncertainty, low competitive intensity, and low state monopolization.

This study is the first to explore why firms prefer exploitative innovation over exploratory innovation from the perspective of EPU. In doing so, this study expands and enriches the EPU literature and the innovation literature. Furthermore, by introducing the moderating role of industry environment, this study deepens the authors' understanding of how complex interactions between industry and institutional environments work together to shape firm strategic choices, and especially firm innovation. Finally, the conclusions of this study have important practical implications for shareholders to take measures to balance exploitative innovation and exploratory innovation to achieve better development.

In light of the current challenges in the business environment, firms, particularly those involved in supply chains, must foster innovation. In this context, the current study employs the theory of dynamic organizational capabilities (DOCs) to track supply chain learning capabilities (SCLCs) and independently uncover their relationship to innovation at both the product and process levels. Similarly, the study intends to investigate the influence of technological turbulence (TT) on these relationships as a moderating variable.

The data were gathered using in-person interviews with 189 CEOs with some supply chain management proficiency from small and medium-sized enterprises (SMEs) in the industrial zones of eastern Egypt. The study used a survey approach to collect data, and the SEM-PLS technique was utilized to analyze the data.

Study findings revealed that SCLCs positively affect product and process innovation. In addition, TT positively moderates the relationship between SCLCs and product and process innovation, except for risk-taking capability. Further theoretical and practical implications are derived from the study findings.

This research adds to the knowledge of the dynamic capabilities theory (DCT), which affects how firms interact with their external environment. Studying learning capabilities are employed as essential competencies to counterbalance high levels of TT in the external environment in terms of innovative performance and vice versa if firms do not attempt to strengthen their dynamic learning capabilities in supply chains. In addition, this study contributes to the literature by studying learning capabilities from the external perspective, where SCLCs are being developed as a new variable to improve innovation.

The purpose of this study is to build a consensus model of social network group decision-making (SNGDM) based on improved PageRank algorithm. By objectively and fairly measuring the evaluation ability of participants in the decision-making process, the authors can improve the fairness and authenticity of the weight solution of decision-makers (DM) in the decision-making process. This ensures the reliability of the final group consensus results.

This study mainly includes six parts: preference expression, calculation of DM's weight, preference aggregation, consensus measurement, opinion adjustment and alternative selection. First, Pythagorean fuzzy expression is introduced to express the preference of DMs, which expands the scope of preference expression of DMs. Second, based on the social network structure among DMs, the process of “mutual judgment” among DMs is increased to measure the evaluation ability of DMs. On this basis, the PageRank algorithm is improved to calculate the weight of DMs. This makes the process of reaching consensus more objective and fair. Third, in order to minimize the evaluation difference between groups and individuals, a preference aggregation model based on plant growth simulation algorithm (PGSA) is proposed to aggregate group preferences. Fourth, the consensus index of DMs is calculated from three levels to judge whether the consensus degree reaches the preset value. Fifth, considering the interaction of DMs in the social network, the evaluation value to achieve the required consensus degree is adjusted according to the DeGroot model to obtain the overall consensus. Finally, taking the group preference as the reference, the ranking of alternatives is determined by using the Pythagorean fuzzy score function.

This paper proposes a consensus model of SNGDM based on improved PageRank algorithm to aggregate expert preference information. A numerical case of product evaluation is introduced, and the feasibility and effectiveness of the model are explained through sensitivity analysis and comparative analysis. The results show that this method can solve the problem of reaching consensus in SNGDM.

Different DMs may have different judgment criteria for the same decision-making problem, and the angle and depth of considering the problem will also be different. By increasing the process of mutual evaluation of DMs, the evaluation ability of each DM is judged only from the decision-making problem itself. In this way, the evaluation opinions recognized by most DMs will form the mainstream of opinions, and the influence of corresponding DMs will increase. Therefore, in order to improve the fairness and reliability of the consensus process, this study measures the real evaluation ability of DMs by increasing the “mutual judgment” process. On this basis, the defect of equal treatment of PageRank algorithm in calculating the weight of DMs is improved. This ensures the authenticity and objectivity of the weight of DMs. That is to improve the effectiveness of the whole evaluation mechanism. This method considers both the influence of DMs in the social network and their own evaluation level. The weight of DMs is calculated from two aspects: sociality and professionalism. It provides a new method and perspective for the calculation of DM’s weight in SNGDM.

This paper investigates whether China's R&D tax deduction policy triggers firms to manipulate their R&D expenditures upward.

This paper employs the ratio of actual tax savings as a proxy for the benefits of the R&D tax deduction policy based on manually collected and systematically cross-checked data. The relationship between tax benefits and abnormal R&D spending is estimated in a sample of Chinese A-share listed companies for the period 2007–2018.

The findings suggest that tax deductions lead to positive abnormal R&D spending and that this deviation in R&D spending may be attributed to firms' upward R&D manipulation for tax avoidance. The results also indicate that this behavior is more significant for the period after the policy revision, in non-HNTEs (high and new technology enterprises), and in firms with a high ratio of R&D expenses.

It is difficult to establish a sophisticated and unified model to identify the specific strategy of upward R&D manipulation that firms use to obtain tax benefits.

Managers should take into account upward R&D manipulation when designing governance mechanisms. Policymakers in developing countries may further pursue preferential tax policies that cover every stage of innovation activities gradually; the local provincial governments need to leverage their proximity and flexibility advantages to develop a tax collection and administration system.

This study contributes to the understanding of the complex effect of R&D tax incentives and helps more fully illuminate firms' upward R&D manipulation behavior from the perspective of tax planning strategies, which are underexplored in previous research.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

Many studies have examined the antecedents of firms' strategic change on a micro and meso level, but few studies have explored it from the macrolevel (e.g. economic policy uncertainty) perspective. This research draws attention to the impact of economic policy uncertainty on firms' strategic change.

This research empirically tests hypotheses based on a sample of listed firms in China during the period between 2010 and 2017.

Based on real options theory, the authors theorize and find that economic policy uncertainty will negatively affect firms' strategic change through the mediating effect of CEO turnover. Moreover, organizational inertia will strengthen the negative impact of economic policy uncertainty on CEO turnover and will weaken the positive impact of CEO turnover on firms' strategic change.

First, this research contributes to the strategic change literature by demonstrating the important impact of economic policy uncertainty on firms' strategic change. Second, this research expands the literature on the economic consequences of economic policy uncertainty. Third, this research clarifies the path and boundary conditions of economic policy uncertainty affecting strategic change by introducing the mediating effects of CEO turnover and the moderating effects of organizational inertia.

Social commerce (s-commerce) offers community-based platforms that facilitate customer-to-customer interactions and the development of customers' social shopping-based experience. While prior research has addressed the role of customer engagement (CE) in boosting s-commerce-based sales and performance, insight into the effect of s-commerce attributes on CE remains tenuous. Addressing this gap, this study examines the role of specific s-commerce attributes (i.e. community, collaboration, interactivity and social dynamics) on CE, which is, in turn, proposed to impact customers' repurchase- and electronic word of mouth (eWOM) intention.

A web-based survey was deployed to target users of a popular s-commerce platform, Etsy.com. Partial least squares structural equation modeling (PLS-SEM) was, then, used to analyze the survey data collected from 390 users.

The results reveal that the four examined attributes positively affect CE. The findings also demonstrate CE's positive effect on customers' repurchase- and eWOM intention.

Though CE has been identified as a key s-commerce performance indicator, little remains known about the role of specific s-commerce attributes in driving CE, as, therefore, explored in this research. Specifically, the authors examine the role of s-commerce-based community, collaboration, interactivity and social dynamics on CE. Their analyses also corroborate that CE, in turn, drives customers' post-purchase (i.e. repurchase/eWOM) intention. Managerially, our findings can be used to develop more engaging s-commerce platforms.

In this paper, the authors study the entry and outsourcing strategies of manufacturer while considering the brand spillover effect resulting from outsourcing. The supply chain comprises two manufacturers: one being the entrant with a strong brand, and the other as the incumbent with a weak brand. The entrant decides whether and how to enter the market.

Stackelberg game is applied to study the optimal strategies for the manufacturers. This paper conducts a comparative analysis on four situations, yielding conclusions and managerial insights.

The results show that, for the entrant, there is no need to worry about the brand spillover effect in the outsourcing process, which is very interesting and counterintuitive. To get further, the authors find the reason: The spillover effect causes the entrant’s equilibrium retail price to grow faster than the wholesale price. They also prove that a stronger brand effect empowers the entrant to challenge industry barriers, while the impact of the brand spillover effect is the opposite. For the incumbent who acts as the weak party in this issue, it is demonstrated that the optimal choice is to continue selling when facing the encroachment and outsourcing call from the entrant.

Differing from previous studies, the authors notice the brand spillover effect caused by outsourcing when studying company’s entry strategy. They further divide the brand effect into two parts, one of which does not exhibit a spillover.

The ability of construction firms to become more environmentally conscious and socially responsible for their business activities has been touted as the key driver for improved individual firms' competitiveness. This study explores the key dimensions of corporate social responsibility (CSR) practices and their impact factors among construction firms.

Through the institutional, stakeholders and self-determination theories, this study proposed a conceptual framework of CSR implementation. For its validation, data were collected from 90 top-tier construction firms using an online survey and analyzed via a two-pronged factor analysis method.

The empirical results demonstrate that the CSR practices of construction firms include eight key dimensions, e.g. shareholders' interests, government commitment and CSR institutional arrangement. The three key groups of impact factor of CSR implementation are (1) identified factors (i.e. contractors' perceived importance of CSR practices); (2) external institutional factors (i.e. coercive and normative factors and mimetic factors); and (3) intrinsic factors (i.e. strategic business direction, resource and capability and organizational culture).

The research findings inform the practitioners about how to enact, manage and improve firms' socially responsible goals so as to fulfill their key stakeholders' requirements and expectations and thus enhance their legitimacy in construction businesses.

This study contributes to CSR knowledge by identifying and empirically demonstrating valid measurements of the key dimensions of practices and impact factors toward CSR implementation by construction firms.