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This study examines the moderating role of information sharing on the effect of lead-time management on the performance of firms in the Zimbabwean motor industry.

Data were collected using Likert-based structured questionnaires from a sample of 105 employees in Zimbabwe. In addition, Pearson Correlation, Linear Regression and Moderation Regression analysis were employed to test the relationship between study variables.

The study found that fixed lead time, preprocessing lead time, processing lead time and postprocessing lead time significantly influence the performance of firms in the motor industry. The results also demonstrate that information sharing moderates the effect of lead-time management on firm performance in the motor industry.

Firms in the motor industry should establish long-term relationships with their suppliers and implement effective communication channels for timely and frequent information exchange regarding production schedules, inventory levels, quality standards and potential disruptions.

The current study aims to contribute to the scientific discourse on lead-time management, information sharing and performance in the motor industry. Furthermore, it extends knowledge on the performance of the motor industry in the African region.

The objective of this study is to understand the mediating role of student engagement between future time perspective and group task performance. In addition, the study examines the interaction effect of group cohesion task with student engagement on group performance.

Data were collected from 170 (a total of 34 groups of five members each) business management students for three consecutive months. To analyze the data, multi-level modeling was carried out.

The results of the three-wave multi-level analysis indicate support for the hypotheses and suggest that future time perspective affects group performance through student engagement. Moreover, group cohesion interacts with student engagement to predict group task performance.

The findings show how the application of engagement theory can help in understanding the relationship between two distant variables, namely, future time perspective and group performance.

The educators are encouraged to engage students for facilitating the positive impact of future time perspective on group task performance. The findings also imply that the students with future orientation perform well and thus, the educators may need to teach students to have futuristic perspective.

This study in one of its kinds to test the mediating role of student engagement between future time perspective and group task performance as well as the interaction effect of group cohesion task with student engagement on group performance at both the individual and group level over a period of time.

The purpose of this paper is to examine the market timing and stock selection abilities of socially responsible (SR) mutual funds. Some high-profile SR fund managers try to embrace market timing and security selection plans to add value to the performance. Market timing relies on forecasting the equity market and shifting assets into or out of the market in anticipation of market movements. The selectivity measure assesses fund managers ability to select undervalued securities. Furthermore, the authors examine whether fund characteristics play any role in market timing and security selection ability.

The authors use Treynor and Mazuy's’ (1966) and Henriksson and Mertons’ (1981) model to examine the market timing and security selection ability. The study uses a decade of monthly returns to examine the skills of fund managers in the SR industry for the period from July 2002 to June 2012.

The main findings are that the managers – though not very successful – do indulge in stock selection and market timing activities. It was found that 48 funds have positive statistically significant stock selectivity coefficients and only a very small number of five funds with positive statistically significant market timing coefficients. Results suggest that there is a trade-off between the two activities. It was found that aggressive funds, funds with higher growth rate and riskier funds are more likely to engage in market timing rather than stock selection.

The implication is that SR managers cannot achieve superior stock selection and market timing ability simultaneously. Risk-averting investors in SR funds expect SR behavior from the managers. This means that managers of SR funds, with very little evidence of market timing ability, may have to refrain from market timing of SR funds.

Using a Morningstar dataset comprising almost all SR funds in existence as of June 2012, this is probably the most exhaustive long-term study to date on market timing and stock selection abilities of SR fund managers.

The purpose of this paper is to generate a performance model for an order‐to‐delivery (OTD) process in delivery scheduling environments. It aims to do this with a triadic approach, encompassing a customer, a supplier and a logistics service provider.

The paper takes the form of a conceptual analysis and a triadic case study on performance measurement requirements in an OTD process characterized by delivery scheduling, and generating performance models.

Two OTD process performance models, one for the supplier's delivery sub‐process and one for the customer's delivery scheduling, the logistics service provider's transportation and the customer's good receipt sub‐process, in delivery scheduling environments are generated.

A single case study limits the levels of external validity and reliability to analytical generalization.

The generated performance models include definitions of four sub‐processes and outline ten performance dimensions that should be of relevance for several companies to apply.

This is the first approach that generates performance models for a triadic OTD process for use in delivery scheduling environments.

The purpose of this paper is to develop a conceptual framework of integrated supply chain model that can be used to measure, evaluate and monitor operational performance under dynamic and uncertain conditions.

The research methodology consists of two stages: configuration of a conceptual framework of integrated supply chain model linked with performance measures and illustration of the integrated supply chain model and delivery performance using a case of dairy industry. The integrated supply chain model is based on a unitary structuring technique and forms the basis for measuring and evaluating supply chain performance. Delivery performance with variation of demand (forecast and actual) is monitored using a fuzzy-based decision support system, based on three inputs: capacity utilization (influenced by production disruption), raw materials shortage and quality of dairy products.

Integration of supply chain components (materials, resources, operations, activities, suppliers, etc.) of key processes using unitary structuring approach enables information integration in real time for performance evaluation and monitoring in complex supply chain situations. In addition, real-time performance monitoring is recognized as being of great importance for supply chain management in responding to uncertainties inherent in the operational environment.

Implementation of an integrated model requires maintenance of supply chain components with all necessary data and information in a system environment such as enterprise resource planning.

The integrated model provides decision-makers with an overall view of supply chain components and direct links that need to be maintained for supply chain performance evaluation and monitoring. Wider adaptation and diffusion of the proposed model require further validation of the model and feasibility of implementation, using real-time data and information on selected performance measures.

Integration of supply chain components across supply chain processes directly linked with performance measures is a novel approach for effective supply chain performance evaluation and monitoring in complex supply chains under dynamic and uncertain conditions.

Implementing enterprise resource planning (ERP) is a challenging task for small- and medium-sized enterprises (SMEs). The purpose of this paper is to develop an integrated decision support system (DSS) for ERP implementation (DSS_ERP) to facilitate resource allocations and risk analysis.

Analytical regression models are developed using data collected through a survey conducted on 400 SMEs that have implemented ERP systems, and are validated by a simulation model. The validated analytical regression models are used to construct a nonlinear programming model that generates solutions for resource allocations, such as time and budget.

ERP implementation cost increases along the time horizon, while performance level increases up to a point and remains unchanged. To maximise or achieve a certain level of performance within a budget limitation, CSFs are prioritised as: project management (highest), top management, information technology, users and vendor support (lowest). SMEs are recommended to concentrate effort and resources on CSFs that have a greater impact on achieving their desired goals while optimising utilisation of resources.

DSS_ERP proves to be beneficial to SMEs in identifying required resources and allocating resources, but could be further tested in case studies for its practical use and benefits.

DSS_ERP serves as a useful tool for SMEs to predict required resources and allocate them prior to ERP implementation, which maximises the probability of achieving predetermined targets. It also enables SMEs to analyse risk caused by changes to resources during ERP implementation, and helps them to be better prepared for the risks.

The research contributes to the scarce research on ERP implementation using scientific methods. A novel nonlinear programming model is constructed for ERP implementation under time and budget limitations, facilitating resource allocations in an ERP implementation, which has not been reported in any previous research. The research offers a theoretical basis for empirical studies of resource allocations in ERP implementation.

Supply chain (SC) configuration has gained increased acceptance as an important issue when evaluating new customization possibilities and this evidence has contributed to the strengthening of the debate between global vs local production locations. This work contributes in enrichment of this topic by studying how local or global SC location decisions influence performances by considering a SC point of view, in terms of cost and time, in traditional and customized productions.

A discrete event simulation approach, based on experimentation through executable configurations, was used to evaluate different SC scenarios for customized as well as traditional products within the footwear industry.

The results indicated that to identify proper SC locations, existing trade-offs between the time and cost performances should be studied, avoiding the evaluation of a single performance independently and, instead, adopting a complete SC point of view while considering these performances.

This evidence has contributed to the reinforcement of the discussion between far-shore destinations vs near-shore production locations. Further studies are encouraged to adopt the present model, in which addition of other variables such as specific manufacturing competences to differentiate suppliers, both local and global suppliers, or the possibility of realizing special types of product customization required by final consumers can be done.

The paper contributes to the academic and practitioners' debate by proposing a systemic approach to assess SCs’ performances in customized contexts and to compare them to traditional collections. Results indicate that cost and time performance must find a balance that does not necessarily correspond to an exclusively local or global production.

This work contributes to the SC configuration issue by considering the trade-off between efficiency and effectiveness (i.e. SC costs and SC times) for customized productions by reviving and enriching it with an SC perspective in customization contexts.

While digital media changed the nature of communication in service contexts, often allowing customers to interact instantly with service providers, the implications and opportunities for managing service employees are widely unknown. This is surprising, given that service employees are an important determinant of service firms’ success. This article examines the effects of real-time performance feedback on employees’ service performance and investigates both how and under what conditions timely feedback encourages employees’ engagement.

Two experiments test the conceptual model and the proposed hypotheses. A field experiment uses real customer feedback gathered after interaction with the app-chat of a large telecommunications provider. It tests the effect of feedback timing on service employees’ performance and also examines the effect of feedback timing on their engagement. A subsequent scenario-based experiment then investigates the influence of selected moderators on the feedback timing–engagement relationship.

This article finds that real-time feedback leads to greater service performance than subsequent feedback. Furthermore, real-time feedback positively affects service employee engagement through the perceived controllability of the feedback and the service situation. Finally, feedback valence, task goals, individuals’ need for closure (NCL), and gender interact with feedback timing to influence employee engagement.

This research investigates the potential of real-time performance feedback for service firms, combines and extends a variety of literature streams, and provides recommendations for the future management of service employees.

The purpose of this paper is to examine the relationship between training and development investment and financial performance over time. Human capital literature suggests that training and development investment may not immediately affect financial performance but may instead create effects that are realized over time. However, most existing cross-sectional research explores the influence of training and development investment on performance while overlooking training and development investment’s long-term effects.

This study focuses on the recovery period following the Great Recession circa 2008 in the South Korean business context. Longitudinal data from 312 firms, including four distinct waves, were used. Latent growth modeling was used to help identify a pattern of reciprocal relationships between training and development investment and financial performance over time.

The results indicate that even though growth in training and development investment is stable over time, there are significant between-firm differences in training and development investment trajectories over time. Prior financial performance was shown to be positively related to higher levels of training and development investment, but it was not related to growth in training and development investment. The initial level of training and development investment did not predict subsequent profit, but growth in training and development investment was positively related to future financial performance.

This study suggests that as an organization’s training and development investment increases over time, a delayed effect on financial performance may emerge because of this accumulated investment. Ultimately, the results highlight the importance of having a stock of human capital, rather than concentrating upon momentary flows that yield immediate effects.