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This study identifies and ranks the appropriate critical success decision criteria (CSDC) for the bulk order distribution (sharing) amongst multiple manufacturers (suppliers) working as an extended enterprise (EE).

The study deploys a qualitative approach to generate the appropriate decision criteria. The balanced scorecard and Pareto's chart (using Minitab^® version 18) were used for gathering and analysing the pertinent criteria.

The process of evaluating and selecting the right manufacturers is essential. Manufacturer (supplier) selection is no longer decided solely based on cost/price criterion; currently, the quality and delivery criteria prevail. Additional incorporated criteria include price/cost, technical capability, production facilities and capacity, customer satisfaction and impression, geographical location, management and organisation, financial position, environmental concern, performance history, repair service, information technology and communication systems, procedural compliance, labour relation record, reputation, flexibility or diversification, attitude, operating controls, business desire, packaging ability, past business records, trust and loyalty, training aids, complaint handling service, warranties and claim policies, reciprocal arrangements, research and development and innovation, modern slavery concern, sustainable capability, collaborative/partnership and responsiveness. The study proposed a conceptual framework of an EE alongside how manufacturers working as a single virtual entity can consider the supply chain operations reference (SCOR^®) model.

The identified CSDC are suitable for order allocation to domestic manufacturers. The deployed approaches could be extended to the mixed and quantitative approaches for increasing the generalisability.

The study establishes the pertinent CSDC that are important to execute equitable order distribution to manufacturers in an EE framework.

The fashion market in the UK is extremely unpredictable. However, there are reliable leading indicators which enable the absolute size of the market to be explained with a high degree of accuracy. The paper is a regression model which explains the value of consumer spending on clothing in the UK for the period 1987‐2000. The model uses changes in income and price to explain changes in spending on clothing. The model works in the sense that it explains over 90 per cent of the observed change in spending and the results are consistent with the expectations of economic theory. Estimates of both income and price elasticity of demand are derived from the model. The latter gives some support to the activities of the so‐called discounters while the former supports the argument that the demand for clothing is wants rather than needs driven.

Wages have been spreading out across workers over time – or in other words, the 90th/50th wage ratio has risen over time. A key question is, has the productivity distribution also spread out across worker skill levels over time? Using our calculations of productivity by skill level for the United States, we show that the distributions of both wages and productivity have spread out over time, as the right tail lengthens for both. We add Organization for Economic Co-Operation and Development (OECD) countries, showing that the wage–productivity correlation exists, such that gains in aggregate productivity, or GDP per person, have resulted in higher wages for workers at the top and bottom of the wage distribution. However, across countries, those workers in the upper-income ranks have seen their wages rise the most over time. The most likely international factor explaining these wage increases is the skill-biased technological change of the digital revolution. The new artificial intelligence (AI) revolution that has just begun seems to be having similar skill-biased effects on wages. But this current AI, called “supervised learning,” is relatively similar to past technological change. The AI of the distant future will be “unsupervised learning,” and it could eventually have an effect on the jobs of the most highly skilled.

The purpose of this paper is to compare the role honor and shame play in honor killings and anti-LGBTQ homicides by identifying similarities and differences across these two homicide types.

This study uses data from the US Extremist Crime Database (ECDB). Data for each of the incidents included in the ECDB are gathered from various open sources through a multi-stage process. A total of 16 honor killings and 21 anti-LGBTQ cases (i.e. the universe for both groups) are examined in this analysis. A closed-coded analysis technique is utilized to assess each case for evidence of shame and honor as well as an iterative coding process to identify sub-categories within these broader themes.

Results indicate that shame and honor play important roles in both honor killings and anti-LGBTQ homicides, although their influence manifests differently across these two types of homicide. Perceived shame to the family is most closely related to honor killings, while suppressing homosexual urges underlines anti-LGBTQ homicides. Violations of religious tenets, protection of masculinity, and protection of honor are evidenced in both types of homicide.

This study uses a unique database to examine the ideological motivations of individuals who perpetrate extremist crimes in comparison to those who commit honor killings. Findings may inform forensic practices, including rehabilitation and prevention programs.

Scholars have widely asserted that a firm’s manufacturing technologies must be aligned with its competitive strategy. This study tests the existence of such a strategy‐technology “fit”, determines whether good fit results in better performance, and examines the nature of fit in light of computer controlled or “advanced manufacturing technologies”. For a sample of 399 metal machining firms, a strategy‐technology alignment was found to exist and relate to higher financial performance. Advanced manufacturing technologies were found to both reinforce and alter conventional thinking about the flexibility‐efficiency tradeoff. Specific technologies were found to be uniquely bundled or combined to support specific competitive requirements.

Based on two dominant perspectives, team climate and knowledge integration, on team innovation, this study aims to propose a moderated mediation model to examine the interactive effect of inter-team trust and goal clarity on team innovation through knowledge inflows into a team. Considering the two perspectives at the same time will provide a more complete picture on our understanding on team innovation.

The research model is tested on 150 retail teams of a large apparel firm. Data are collected from two separate surveys, one to store managers and one to store staff members. Moderation mediation regression analysis is conducted on the survey data.

The regression analysis identified both a positive direct effect of goal clarity on innovation, and a negative moderating effect of goal clarity on the mediation of knowledge inflows between inter-team trust and innovation. In other words, inter-team trust is positively related to team innovation through knowledge inflows when goal clarity is low.

In this study, the authors identify an indirect and negative role of goal clarity on team innovation, and examine the mechanism and boundary of inter-team trust on team innovation. Managers are advised to foster a trusting environment and be aware of cognitive bias in their teams so that their teams can be more innovative.

The purpose of this paper is to examine the relationships between different managerial roles and organization-based self-esteem (OBSE), and employee job satisfaction, organization commitment, and turnover and absence intentions.

Survey data were collected from 1,386 employees in a high technology industry. Employees described the roles their managers fulfilled, and then rated their own OBSE, satisfaction, commitment, and turnover and absence intent.

Different managerial roles had different relationships with OBSE, which mediated the relationships between some of the management roles and employee outcomes.

This study used a cross-sectional design with single source data in a single industry. Future research should examine these relationships using longitudinal designs, multiple data sources, and a variety of industries.

Managers should be aware that their behaviors affect employee self-esteem, which in turn has strong relationships with a variety of important outcomes. Managers should be trained to manifest behaviors that increase employee self-esteem.

This is the first study to examine the effects of management roles on organization-based self-esteem, and ultimately employee satisfaction, commitment, and withdrawal intentions.