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The purpose of this paper is to understand how buyers and suppliers in supply chains learn to align their performance objectives and incentives through contracting.

Two longitudinal case studies of the process of supply chain alignment were conducted based on 26 semi-structured interviews and 25 key documents including drafts of contracts and service level agreements.

The dynamic interplay of contracting and learning contributes to supply chain alignment. Exchange-, partner- and contract framing-specific learning that accumulates during the contracting process is used to (re)design pay-for-performance provisions. Such learning also results in improved buyer-supplier relationships that enable alignment, complementing the effect of contractual incentives.

The study demonstrates that the interplay of contracting and learning is an important means of achieving supply chain alignment. Supply chain alignment is seen as a process, rather than as a state. It does not happen automatically or instantaneously, nor is it unidirectional. Rather, it is a discontinuous process triggered by episodic events that requires interactive work and learning.

Development of performance contracting capabilities entails learning how to refine performance incentives and their framing to trigger positive responses from supply chain counterparts.

The paper addresses supply chain alignment as a process. Accordingly, it stresses some important features of supply chain alignment.

Examines the use of learning contracts to achieve supervisory development in an organization with highly centralized decision‐making processes and a strong power‐based culture. Shows that a well‐managed learning contract process can significantly increase the value of supervisory development and help to facilitate more consensus‐ and collaborative‐based approaches to problem solving and encourage learning in the ongoing work activities of the organization.

The purpose of this study is to examine how formal contracts affect alliance innovation performance. To understand the mechanism underlying the impact, this study tests whether relationship learning mediates the impact of formal contracts on alliance innovation performance and how guanxi moderates the mediating effect.

This study is conducted with a sample of 225 manufacturers in China. This paper used hierarchical regression analysis to test the hypotheses and used the PROCESS method to test the mediating effect of relationship learning.

Formal contracts positively affect relationship learning, which facilitates alliance innovation performance. Guanxi positively moderates the effect of formal contracts on alliance innovation performance. Relationship learning mediates the relationship between formal contracts and alliance innovation performance. Moreover, guanxi positively moderates the mediating effect.

Future research could investigate factors moderating the effect of guanxi on alliance innovation performance and moderating the effect of relationship learning on alliance innovation performance. Future research can also use secondary data to measure alliance innovation performance. Future researchers can examine how guanxi as a relational mechanism governance affects relationship learning.

Managers should conduct relationship learning in the process of alliance innovation and realize that reducing opportunism does not mean improving innovation performance. Moreover, managers should know that guanxi could contribute to alliance innovation performance with the help of formal contracts.

Prior studies have mainly focused on the fundamental requirement of governing knowledge exchange in alliances. Little is known about the mediating effect of relationship learning on the relationship between formal contracts and outcomes of innovation alliances. This study contributes to the literature by filling the gap.

The purposes of this study are twofold. First, to theoretically examine the profit-sharing (mudarabah) contract that produces an optimal distribution of return in the presence of social learning (shuratic process) within the environment of asymmetric information. Second, to empirically investigate the optimal condition of profit-sharing ratio (PSR) and social learning for profit-sharing (mudarabah) contract in Islamic banking.

Data from one of the biggest and earliest Islamic banks in Malaysia were taken as a proxy of an Islamic bank. The data are collected from the period of 2009 to 2013, and these will be used for the simulation process by using the genetic algorithm (GA) technique.

The empirical results discovered that Islamic banks had used social learning in their daily activities, especially in the asset side. The results also showed that the trend of social learning has a positive relationship with the trend of Islamic banks’ net profit. Additionally, the results also indicated that the Islamic banks’ net profit has a positive relationship with its PSR from the profit-sharing (mudarabah) financing and securities investment.

This study is the first of its kind that investigates the implementation of the social learning process in Islamic banking operation. This study also used the latest technique from artificial intelligence system, i.e. a GA, to attain an optimal value for PSR and social learning process.

This paper investigates how symmetrical learning activity is, between the public client and the private contractor in the contracting and operation of complex, long-term infrastructure projects. Drawing on empirical material from two United Kingdom (UK) private finance initiative (PFI) cases, the paper analyses differences in the absorptive capacity and learning capability between parties. It suggests the private contractor appears to be better equipped to acquire, embed and renew their learning. These findings reflect less than 5 years of a 30-year contract, suggesting a skewed (imbalanced) relationship, where the contractor gains more learning capabilities than the client. The paper concludes with implications for management practice and suggestions for future research directions.

Describes an aspect of the work on quality in open learning undertaken by the SATURN quality sub‐group. Argues that a key to the achievement of quality in learning is the setting of clear expectations of what is required, both of providers and users in learning contracts. Lists codes of practice for both providers and users and defines provider and user groups. Discusses the use of the codes in developing an individual learning contract for the three stages in a learning contract‐before, during and after.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

The purpose of this paper is to highlight some of the issues involved in ensuring that final year undergraduate students have a meaningful WBL experience as part of their business degree. It originated in discussions between the authors concerning varying attitudes towards the idea and practice of WBL in business schools. The study examines examples of artefacts produced for assessment, as well as perceptions of the practice of WBL through an exploration of the perspectives and views of students and employers. Material was also gathered from the reflections of the authors in their capacity as WBL supervisors.

This paper draws on a qualitative research study which used semi-structured interviews to obtain views on a range of issues associated with WBL, including the nature and scope of what is learnt and acted upon in the workplace and the value of the learning contract. The data comprise semi-structured interviews with 13 graduates of a post-1992 UK university and with five employers. The authors also reflect on their experience in delivering the WBL unit.

This study examines some key issues associated with WBL. It supports the idea that unintended, informal and even “tacit” knowledge may be effectively reflected upon and assessed; that learning contracts play an important role in WBL arrangements and do not necessarily restrict or constrain what is learnt or how that learning is developed, and that artefacts provide the bridge between knowledge and work.

Employer feedback was limited, and despite attempting to contact all WBL graduates, only 13 responded and were able to be interviewed. The findings will be helpful to different stakeholders engaged in WBL who wish to develop effective strategies to maximise the benefits of WBL. The findings of this research relate to different elements in the process including the value of the employer-led project and the evidence of real improvements/contributions made in delivering their artefact, of the learning contract as a “live” document and the value of informal, experiential learning in the process.

The findings will be helpful to different stakeholders engaged in WBL who wish to develop effective strategies to maximise the benefits of WBL.

The paper offers a contribution to our knowledge and understanding of perceptions of the actual practice of business students’ WBL.

A recent report has suggested that there is a total inadequacy of management education and development in Britain. One fundamental concern is the design of programmes which focus on the development of effective managers, as opposed to just teaching people about business and management. An innovative management development programme has been developed, based around key adult learning principles such as emphasis on management competencies and work experience based learning.

This is the first in a series of three articles which evaluate the use of self‐managed learning (SML) in management development processes in health care settings. This first article, being more general, outlines SML′s philosophical origins, strategic design, and current practice. SML represents a strategic approach to individual and organizational learning, which offers a new synthesis of previous ideas and approaches. Its proven benefits relate to the way in which the process of learning is designed to mirror the process of managing. The second article focuses specifically on a regional NHS case study of the application of SML, while the third provides a complementary US case study in a health care provider organization, where SML has been adopted for a leadership development programme.