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This paper aims to assess the comparative position of the national innovation system of Chinese state entrepreneurship versus liberal market entrepreneurship. Based on the comparative institutional framework, it asks whether Chinese state entrepreneurship has a comparative disadvantage because of its incoherent institutions in liberal or coordinated economies. Hence, does the Chinese institutional system of innovation lag behind that of US or liberal countries of Organisation for Economic Co-operation and Development (OECD) economies in the transformation of national science into economic products measured as high-technology exports?

This study uses panel data analysis based on 29 OECD economies and the Chinese economy over 23 years. Regarding national science productivity (explorative capabilities), it includes published and patented science streams; regarding technological transformation (exploitative capabilities), it measures the percentage of high-technology exports in gross domestic product (GDP). The interactions between the types of entrepreneurship and national science institutions serve as predictors in the design.

The results show that Chinese state entrepreneurship has a comparative advantage over liberal economies in published science. However, Chinese state entrepreneurship has a comparative disadvantage compared to liberal entrepreneurship in patent science. Regarding the dyadic level of comparability between the national economies, there are mixed results in the transformation of national science.

This study supports the three following theoretical points: national institutions differ regardless of the pressure of convergence through globalization; national science contingencies influence different paths of the transformation of national science to technology; and mixed economies, such as state entrepreneurship, can achieve high performance without fully conforming to liberal markets.

This study emphasizes institutional mechanisms for future research to support the innovation of incoherent institutions and suggests the benefit of cross-pollination of senior managers between state and private organizations for a defined duration.

Theoretically, this research combines an interdisciplinary and interinstitutional level of analysis, and in so doing, it deals with the transformation of national science in scientific publications and patents in the vertical value chain. Empirically, this study links the national published and patented science with the national economic artifacts in high-technology sectors. This novel approach to assess the national and discipline-level interaction sets a context for the future research in other settings. It also informs policy decisions regarding the growth of science, innovation and development.

In this paper, we examine the comparative advantage of Korea and China while focusing on their technology level. The three digit SITC (Standard International Trade Classification) data is classified by technology level and the revealed comparative advantage (RCA) is derived from 1992-2009 by using UN COMTRADE data. For careful interpretation of the comparative advantage and technology levels, we also examined intra-industry trade and unit values of bilateral Korea-China trade, and semi-conductor industry technology. We found that the revealed comparative advantage has moved from low technology products to high technology products in Korea. China still maintains a comparative advantage in low technology products such as textiles and clothing, but at the same time, China’s high and medium-high technology products have recently gained a comparative advantage. The perception that China only has a comparative advantage for labor intensive products with low technology should be changed based on our analysis. However, China’s advancement in technology should not be overestimated. When comparing the unit value of basic materials of Korea’s and China’s exports, we found that Korea’s export product prices are on average higher than that of China’s, although the gap is reducing. A wider technology gap between Korea and China still exists in the semi-conductor industry, which is one of the most advanced high technology industries throughout the world.

Practices of transfer pricing in among companies having “special relationship” (hubungan istimewa in Bahasa Indonesia, this study uses a term of ‘related party’) to others are very common nowadays. However, the complexity of transfer pricing strategy and practices in many companies made the use of individual level data become insufficient, therefore we conduct an ethnographic study to explore how taxpayer determines the reasonable transfer pricing based on five methods (i.e. Comparable uncontrolled Price/CUP, Resale Price/RPM, Cost Plus, Transactional Net Margin Method/TNMM and Profit Split Method/PSM).This research aims to execute a tax strategy based on those methods, which finally derive the amount of product price according to arm.s length transfer pricing rule. We collected the data through interviews, observation and literatures. They are based on several months of personal experience of field research in and around the manufacturing enterprise. The results showed that the tax expense could be reduced by using Cost Plus Method, but practically, the application of this method requires more in-depth analysis and a very reliable & comparative data so the company must spend a lot of cost and time to process it. The Transactional Net Profit Method is proved to be the best application for the enterprise to optimize tax expenses because the data used for the analysis were more accessible which saved time and costs.

With an increasing air cargo demand in the global air cargo transport industry, not only domestic airlines but also foreign carriers are actively investing in the air cargo service sector and trying to provide a differentiated service in order to gain a competitive advantage. There are a variety of service quality models available but most research to date has not found an optimal model for the air cargo service sector.

Using questionnaire data collected from air freight forwarders in Korea with respect to the air cargo service provided by Korean Air, Asiana Airlines, and foreign carriers(JAL or China Eastern), this paper compares four models in measuring the service quality in the air cargo sector and identifies the best model. We then analyze the weakness of each airline’s service operation and make suggestions for improvement.

For demonstration analysis, the survey of domestic air cargo forwarders revealed that Reliability>Responsiveness> Supply ability>Security in important order in air cargo service quality dimension. In the context of this paper, we considered four models-unweighted SERVQUAL, unweighted SERVPERF, weighted SERVQUAL, and weighted SERVPERF–for our investigation into which is the most suitable model in the air cargo service sector with testing of goodness of fit by three criteria. Our results indicate that the most suitable model for the air cargo service sector is the weighted SERVPERF model.

International Journal of Emerging Markets (IJoEM) is a leading journal that publishes high-quality research focused on emerging markets. In 2020, IJoEM celebrated its fifteenth anniversary, and the objective of this paper is to conduct a retrospective analysis to commensurate IJoEM's milestone.

Data used in this study were extracted using the Scopus database. Bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of a journal. Mapping of bibliographic data is carried using VOSviewer.

Study findings indicate that IJoEM has been growing for publications and citations since its inception. Four significant research directions emerged, i.e. consumer behaviour, financial markets, financial institutions and corporate governance and strategic dimensions based on cluster analysis of IJoEM's publications. The identified future research directions are focused on emergent investments opportunities, trends in behavioural finance, emerging role technology-financial companies, changing trends in corporate governance and the rising importance of strategic management in emerging markets.

To the best of the authors' knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJoEM. The study presents the key themes and trends emerging from a leading journal considered a high-quality research journal for research on emerging markets by academicians, scholars and practitioners.

This study aims to investigate the logistics service quality (LSQ) from a supply chain quality perspective. The purpose is twofold: (1) to investigate how business customers perceive the LSQ dimensions in business-to-business (B2B) relationships, with a particular focus on the role of logistics service providers and (2) to analyse the manner in which such dimensions, when combined, lead to high levels of customer satisfaction.

Data collected through a survey of a sample of Italian food companies are analysed using a qualitative comparative analysis approach. The analysis explores ways of achieving customer satisfaction through different combinations of LSQ dimensions and not only via a “single recipe,” as in most symmetrical methods.

The study describes how seven dimensions of LSQ lead to achieve customer satisfaction, particularly highlighting and discussing how the different LSQ constructs lead to gain high customer satisfaction via different configurations. This approach is unique in identifying not only linear relationships among variables as traditional statistical methods do, via a configurational approach.

Most academic studies in the related literature investigate service quality from a quality management and a supply chain management perspective. This study fills the existing gap in the analysis of B2B relationships, focusing on the role of third-party logistics (3PL) service providers.

The study presents useful implications for practitioners, describing several ways in which 3PL service providers can combine LSQ dimensions to perform a continuous improvement of customer experience and to gain higher levels of customer satisfaction.

This study fills the existing gap in the analysis of B2B relationships, using the lens of quality management and supply chain management perspectives, and focusing on the role of 3PL service providers.

The COVID-19 pandemic and recent disruptive events are affecting firms’ operations and supply chain networks on a large scale, causing disturbances in supply, demand, production and logistics activities. Although supply chain resilience (SCR) research has received large attention in recent years, the purpose of this paper is to offer an original contribution by exploring how complex configurations and interactions between SCR strategies and capacities can lead to resilience.

This study investigates the configurations of SCR strategies and capacities using a fuzzy-set qualitative comparative analysis.

First, the findings reveal different SCR strategy configurations through the lens of absorptive, reactive and restorative capacities to achieve resilience. Second, this study applies the contingent resource-based view (CRBV) perspective to interpret how organizations can achieve resilience before, during and after a disruptive event. Third, it offers an analysis of different groups of organizations, based on the adoption of different SCR strategies and capacities.

This study identifies a set of equifinal SCR strategies and capacity configurations that can be implemented to cope with a disruptive event and lead to resilience. It also enriches the research addressing the consecutive phases of SCR investments, developing the CRBV perspective. In our results, five solutions describe organizations that invest in absorptive capacities, representing an ex ante readiness.

The paper analyzes the response of agricultural value added to credit and real interest rate shocks in the West African Economic and Monetary Union (WAEMU) and make a short-term comparative effect analysis of credit granted to the agricultural sector on agricultural value added among member countries.

First, in order to estimate impulse response functions (IRFs) and study shocks, a panel VAR model is used. Second the paper uses an autoregressive distributed lag (ARDL) model with the associated error correction model to make a comparative analysis of the effect of agricultural credit on agricultural value added in the WAEMU.

Results shows that: (1) credit stimulates agricultural value added only in the medium and long term; (2) in the case of WAEMU, credit only becomes a means of lifting the constraint of capital underutilization after three years; (3) short-term credit granted to agriculture in WAEMU has a weak and differentiated effect on agricultural value added from one country to another.

It is imperative to implement a policy of lowering real short-term interest rates. Moreover, a monetary policy that favors direct financing of agriculture to the detriment of that oriented toward market financing is to be prioritized.

The originality of this paper is that it makes the link between macroeconomics and agriculture. It shows how the monetary instrument can be manipulated to improve the performance of agriculture. Actually, in WAEMU, the financing of agriculture is provided by the market. This paper proposes a new approach which is direct financing. The paper offers possibilities for the coordination of agricultural policies in the WAEMU.

Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance.

This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA.

The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness.

The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances when some of the other knowledge-based partner attributes are considered. Despite these insights for alliance and coopetition literature, some limitations are to be noted. First, some of the partners’ attributes considered could be further disentangled into sub-partner attributes. Second, other indicators might be used to measure firms’ innovation performance. Third, as anticipated this study applies fsQCA to explore the combinatory effects of partner attributes in the specific context of R&D alliances in the telecom industry worldwide and in a specific time window. This condition may question the extensibility of the results to other industries and times.

This study also bears two interesting implications for alliance managers. First, the paper suggests that R&D alliance managers need to be aware that potential alliance partners have multiple attributes leading to firm innovation performance. In this regard, partner competitive overlap is particularly important for gaining a better understanding of firm innovation performance. When looking for strategic partners, managers should try to ally with highly competitive enterprises so as to access their more innovative knowledge. Second, the results also highlight that this beneficial effect of coopetition in R&D alliances can be amplified in two ways. On the one hand, when the partners involved in the alliance have not yet developed experience in forming alliances. Partners without previous experience supply ideal stimuli to unlock more knowledge in the alliance because new approaches to access and develop knowledge in the alliance could be explored. On the other hand, this paper detects the situation when the allied partners are developing technologies and products in different areas. When partnering with firms coming from different technological areas, the knowledge diversity that can be leveraged in the alliances could drive alliance managers to generate synergies and economies of scope within the coopetitive alliance.

Extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance but has concurrently underestimated the configurations of partner attributes leading to firm innovation performance. Therefore, this paper differs from previous studies, as it provides an understanding of the specific configurations of R&D alliance partner attributes leading firms involved in R&D alliances to achieve high innovation performance.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.