The establishment of industrial branding through dyadic logistics partnership success (LPS): The case of the Malaysian automotive and logistics industry

Logistics partnerships across dyadic and triadic relationship networks have been the basis of extensive research in the extant literature. It is well understood that competitive advantage within logistics and distribution and within supply chains are driven by value-adding aspects of not only the core competencies of each tier in the network, but also via tangential supporting factors. It is also well understood that there is a strong relationship between logistics and distribution and marketing functions, particularly in product-based organisations. In addition to deepening our understanding of how successful partnerships throughout the source–make–deliver continuum can be optimised, this research also seeks to identify how a supporting element in terms of industrial branding and marketing can lead to relational sustainability. Hence, this paper outlines the relationship between logistics partnership success (LPS) factors and the inherent link to industrial branding establishment and business sustainability within the Malaysian automotive industry (specifically, car manufacturers). Adopting a multiple case study approach, findings suggest that there is a strong association between logistics service performance (LSP) provided by the third party logistics provider (TPLP) and the development and support of a mutual brand image for both the TPLP and the car manufacturer. We contribute to the extant literature on logistics partnership and industrial branding through linking LSP with the creation and maintenance of an industrial branding strategy for both parties in the context of the Malaysian automotive industry.     

Antecedents of green behavioral intentions: a cross‐country study of Turkey,Finland and Pakistan

Quality of life of the future generations depends on the efforts of current generations to protect environment. The purchase decisions based on their green behavioral intentions not only helps the society, but also helps companies to gain a green competitive advantage. In this study, the relationships between green satisfaction, green trust, green equity and behavioral intentions are examined. Data were collected from Turkey, Finland and Pakistan with self‐administered questionnaires regarding with green white goods. The hypotheses were tested with structural equation modeling. Results of a structural model reveal positive relationships green satisfaction, green trust and green brand equity across three countries. In addition, green brand equity plays a remarkable role in behavioral intentions towards green white goods in general. Managers should consider green trust, green satisfaction, and green brand equity while implementing green marketing strategies in a global marketplace.     

中国农村信用的演化路径研究

中国农村信用是通过自发的、松散的非正式组织形式实现的,在基于血缘、地缘关系的特殊信任主义系统里,农村信用的实施机制和信用保护机制事实上是在一个关联博弈中进行的。当农村非正式社会结构向正式社会结构转轨时,由于契约的法律执行机制的不完善以及交易范围的扩展诱致的信息不完备和非对称,使得关联博弈和信息完备性的基础逐渐丧失,仅靠声誉和关系交易的维系成本急剧上升,人格化交易面临规模不经济和信用风险的双重约束。     

R&D and regional competitiveness: a study of global entrepreneurial firms

We quantify, using data from the World Bank’s Enterprise Surveys and the World Economic Forum’s Global Competitiveness Index, the empirical relationship between global competitiveness and R&D investment activity as well as the independent relationship between global competitiveness and R&D investments across geographic regions of economic development. We also explore alternative measures of the effectiveness of R&D investments. Our findings suggest that R&D investments are a possible policy target variable in high-income regions for policy makers to consider for increasing firms’ global competitiveness.

     

Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China

The current research aims to launch effective accounting fraud detection models using imbalanced ensemble learning algorithms for China A-Share listed firms. Based on a sample of 33,544 Chinese firm-year instances from 1998 to 2017, this research respectively established one logistic regression and four ensemble learning classifiers (AdaBoost, XGBoost, CUSBoost, and RUSBoost) by 12 financial ratios and 28 raw financial data. Additionally, we divided the sample into the train and test observations to evaluate the classifiers' out-of-sample performance. In detail, we applied two metrics, namely, Area under the ROC (receiver operating characteristic) curve (AUC) and Area under the Precision-Recall curve (AUPR), to evaluate classifiers' discriminability. In the supplement test, this study put forward an algebraic fused model on the basis of the four ensemble learning classifiers and introduced the sliding window technique. The empirical results showed that the ensemble learning classifiers can detect accounting fraud for the imbalanced China A-listed firms far more effectively than the logistic regression model. Moreover, imbalanced ensemble learning classifiers (CUSBoost and RUSBoost) effectively performed better than the common ensemble learning models (AdaBoost and XGBoost) in average. The algebraic fused model in the supplement test also obtained the highest average AUC and AUPR among all the employed algorithms. Our results offer firm support for the potential role of Machine Learning (ML)-based Artificial Intelligence (AI) approaches in reliably predicting accounting fraud with high accuracy. Similarly, for the Chinese settings, our ML-based AI offers utmost advantage in forecasting accounting fraud. Finally, this paper fills the research gap on the applications of imbalanced ensemble learning in accounting fraud detection for Chinese listed firms.     

Consumer ethics: A review and research agenda

Consumer ethics continues to draw the attention of academicians and practitioners as a significant economic and social issue globally. Consumer ethics refers to moral principles that govern a consumer's behaviour. This literature review seeks to enrich the discourse on consumer ethics through a comprehensive and detailed review of 106 articles, covering 21 journals from 2010 to 2020. Through an examination of theories, contexts, characteristics, and methodologies used in consumer ethics research, our review (1) presents a comprehensive and up-to-date overview of the research in this field and (2) sets a future research agenda to spur scholarly research. We found studies have primarily relied on a single theoretical lens such as the theory of marketing ethics, planned behaviour, and neutralization theory. Further consumer ethics research focuses on advanced countries, with a narrow focus on developing countries. We have diagnosed the need to examine boundary conditions impacting consumer ethics. Finally, we provide actionable inputs to combat unethical consumer actions as well as promote ethical consumption.     

IRS Private Letter Rulings: Initial Evidence on Determinants and Consequences

This study examines the determinants of firms' requests for Private Letter Rulings (PLRs) from the US Internal Revenue Service (IRS) and their impact on firms' cash holdings. Our results show that PLR requests tend to be made by firms with more active tax planning, more acquisitions, higher analyst following, higher leverage, and less in-house tax expertise. We also show that firms with IRS audit red flags are less likely to request a PLR. We use a difference-in-difference approach to assess changes in cash holdings following PLR requests and report a decrease in cash holdings for PLR firms, consistent with the notion that PLRs act to reduce tax uncertainty. Our study provides the first empirical evidence about the determinants of PLR requests and complements prior work on tax uncertainty and cash holdings (Hanlon, Maydew and Saavedra, 2017).