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The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

The purpose of this paper is to compare the relative impacts of trust and risk on individual’s transaction intention in consumer-to-consumer (C2C) e-marketplaces from both the buyers’ and the sellers’ perspectives.

Two surveys were used to collect data regarding buyers’ and sellers’ perceptions and transaction intentions at a typical C2C e-marketplace. Partial least squares was used to analyze the data. A complementary qualitative study was conducted to triangulate the results from the quantitative study.

Institution-based trust (IBT) exerts a stronger influence on transaction intentions for buyers than for sellers. Sellers perceive a stronger impact of trust in intermediary (TII) than buyers on transaction intentions. The impacts of perceived risk in transactions are not different between buyers and sellers. Furthermore, IBT mediates the impacts of TII and perceived risk on transaction intentions for buyers.

The results indicate that the impacts of trust and risk on transaction intention in e-marketplaces do differ between buyers and sellers. This suggests a need to further investigate the buyer–seller difference in online transactions.

Intermediaries need to focus on different types of trust-building mechanisms when attracting buyers and sellers to make transactions in the e-marketplace.

C2C e-marketplaces cannot survive without participation from both buyers and sellers. Most prior research is conducted from the buyers’ perspective. This research sets a starting point for future research to further explore the differences between buyers’ and sellers’ behavior in C2C e-commerce environments.

The purpose of this paper is to consider the following problem: the authors consider a new constructed unit system to indicate the characteristics of the inputs and outputs of different decision-making units (DMUs) and propose several modified models to calculate their efficiencies based on overall value judgment and weight restriction in the production process.

This paper applies principal component analysis (PCA) to analyze the original value judgment information, and the key indices in the production process are extracted. The modified data envelopment analysis (DEA) models are proposed and DEA efficiencies and their projections are calculated.

By incorporate PCA and DEA, the authors propose new virtual DMUs composed of unique optimal multipliers of each DMU. Crucial indexes are extracted and the weights of inputs and output are ranked through using PCA by taking the preference and value judgments of all DMUs into consideration. Weight constraints from the ranking are utilized to improve the traditional CCR-DEA model. The empirical results validate the feasibility of the approach.

The method can be used in many organizations which have excessive amounts of inputs and outputs variables, such as banks, chain stores, car factory, etc.

This paper presents an integrated methodology of using PCA and DEA for considering the preferences of the inputs and outputs and value judgment of all DMUs and ranks the importance of the indicators from the overall perspectives.

With rapid social development and deepening division of labor, more and more complex projects are required to be carried out in a team form. When evaluating team performance, previous research has usually treated team as a united entity. However, the operating environment of the team has a significant impact on its members and the interaction between them greatly influences the team's efficiency. To better evaluate team performance, we propose a circle loop to illustrate the relationship between the operating environment of the team and its members. A two-stage DEA model with feedback is developed to evaluate the team performance, together with the efficiencies of the operating environment and team members as well as their impacts on overall efficiency. Various conditions of the team are discussed to illustrate that team performance depends on the assumption of the conditions.

This chapter examines the development of accounting thought and practices in China with the purpose of illustrating its relevance to current accounting policies and practices. The review indicates that changes in accounting in China did not usually occur completely and easily. Over the past three decades, while Chinese accounting has gradually moved toward the Anglo-American model, convergence has presented unique features in China. For example, the review suggests that the accounting reforms in China have been heavily government-driven and that uniform accounting systems still remain. Chinese regulators maintain a cautious attitude toward the application of fair value and professional judgment, which are essentially the center of the Anglo-American accounting system. Furthermore, Chinese accounting regulators have a different view of business combinations from the IASB and have developed alternative accounting methods for those transactions. China’s departure from IFRS reflects its politico-economic context and essentially challenges the IASB’s goal of achieving international accounting convergence. China’s approach to internationally acceptable practices is likely to have implications for the effectiveness of the imported ideas.

As a Data Envelopment Analysis (DEA) extension tool, cross-evaluation method was developed to evaluate Decision Making Units’ (DMUs) performances in a competitive situation with limited demand. It identifies DMUs with best performances and rank them by applying peer evaluation mode instead of self-evaluation mode. However, it has limitations in efficiency improvement. That is, it fails to give direct information on how to improve efficiencies of the inefficient DMUs. In this chapter, we propose an alternative way to apply cross-evaluation in efficiency improvement. First, an appropriate and feasible suggestion is proposed to minimize the variation between the weights of a DMU's own optimal Charnes-Cooper-Rhodes (CCR) efficiency and the weights guaranteeing its cross-efficiency score. We exploit several transformations to convert nonlinear programming into a linear one. As a result, an overall optimal set of the weights is obtained, which precisely illustrate the preferences of decision makers and exact characteristics of production process of the evaluated DMU. A further discussion is advanced to examine the existence of non-uniqueness of the weights and to differentiate various sets of the optimal weights by suggesting a unique feasible set of multipliers to best represent the alternative weights selection criterion. Moreover, we develop several models to reallocate the inputs and outputs of inefficient DMUs with minimum amelioration as well as consideration of the preference of decision makers. Finally, we apply our models to evaluate competitive advantages of Chinese cities.

This paper discusses why the MARC21‐based authority format has failed in a global setting and details the use of XML and its related technologies to achieve global name access control.

The banking industry plays a key role in China's financial industry. In the past decade, the speed of the development of China's commercial banks has gradually declined. Commercial banks with different ownership structures also have certain differences in terms of operating efficiency, and their monetary policies are often different. Therefore, the authors study the impact of ownership structure on the efficiency of commercial banks under different monetary policies. This study also provides relevant reference opinions with regard to the healthy, sustainable and stable development of China's banking industry.

This paper mainly uses the two-stage data envelope analysis (DEA) model under meta-frontier and group frontier to study the deposit and loan efficiency changes of 16 banks from 2007 to 2014 under ownership structure heterogeneity. Furthermore, the model introduces the balance parameters between deposits and loans, in order to realize the mathematical abstraction description of macro-monetary policy.

First, based on bank efficiency analysis, the paper finds that most banks' loan efficiency is higher than their deposits. Second, the paper concludes that different monetary policies have little effect on bank deposit and loan efficiency, while ownership heterogeneity has a significant impact on bank performance. Finally, through the decomposition of the sources of inefficiency in bank performance, this paper finds that management and technology are two factors that affect the inefficiency of banks.

The authors work contributes to the existing literature in the following ways: First, to the best of the authors’ knowledge, this is the first attempt to use the DEA model to study the relationship between monetary policies and bank supply chain efficiency. The results may provide additional managerial implications for the banking industry from the perspective of monetary policies. The result is helpful in terms of explaining how and why banks should strengthen risk management, as well as how to deal with non-performing loans in management terms and finally, why banks should make financial technology innovations in technology terms.