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Levels of selected essential and non‐essential metals (Cd, Cr, Pb, Cu, Fe and Zn) and those of macro‐nutrients (Ca, K, Mg and Na) are estimated in 15 different seasonal fruits available in local Pakistan markets. The wet digestion oxidation method was used for the analysis of samples by the flame atomic absorption technique. The results indicated almost 100 percent incidence of occurrence of trace metals and macro‐nutrients in all fruits. The highest concentration was observed for zinc, ranging between 0.13 and 79.9mg/kg, wet weight, respectively for banana and mango. The iron levels ranged from 0.55 to 44.8mg/kg, wet weight, for pomegranate and mango. The concentrations of Cd, Cr, Pb and Cu remained at marginal levels, except for certain fruits where the concentrations were very high. The data are compared with allowed safe limits laid down by WHO.

This research examines micro‐enterprises pursuing gradual growth. While very little research has been targeted specifically at the growth of micro‐enterprises, there are a host of possible influencing factors suggested by the rather broader small business literature. Less research has attempted to integrate the factors that influence growth of small firms into some form of model. Those models that were found had a number of shortfalls when it came to understanding the development of micro‐enterprises. A framework has been developed through this research that addresses these shortfalls. First, it has targeted specifically gradual growth micro‐enterprises; secondly, it is rigorously under‐pinned through empirical research; thirdly, it attempts to comprehensively cover the range of factors that influence development; fourthly, it focuses on the complex interaction of factors that may influence development. The research findings and implications are presented in two parts. Part 1 develops an empirically verified framework that explains how growth is influenced by a myriad of interacting factors. This leads to a discussion of the policy implications of the framework. Part 2 is presented in the next edition of the Journal of Small Business and Enterprise Development (JSBED) and will explore the managerial implications of the framework. This will provide a diagnostic toolkit to help micro‐enterprise owner‐managers and advisers pursue growth. The paper is derived from research conducted initially for the submission of a PhD thesis at the University of Brighton (Perren, 1996).

The purpose of this paper is to examine franchisees’ business start-ups from an entrepreneurial perspective, adopting a process representative of entrepreneurship to examine opportunity identification and evaluation by franchisees and to analyse factors that influence this process.

A qualitative study was employed and data collected using semi-structured interviews with a sample of service industry franchisees in Macau.

The study identifies that social networks play a key role in opportunity identification and that franchisees’ goals influence the criteria used and information search activities undertaken while evaluating franchise opportunities.

The study makes two contributions to franchise literature. It identifies that social networks can serve as substitutes for lack of prior knowledge in franchise opportunity identification. It also identifies the interrelated nature of franchisees’ goals based on the activities and criteria used to evaluate franchise opportunities, and the importance of relational criteria when franchisees lack prior industry knowledge. It therefore also contributes to franchise/entrepreneurship literature by identifying the interrelated nature of the factors contributing to the dynamics of franchise chain growth.

Franchisors should explore how to better use franchisees’ social networks and identify the longer term goals of prospective franchisees to support market penetration and franchise chain growth. Franchisees are advised to use independent information sources to evaluate franchise opportunities using goal-informed objectives and demand and relational criteria.

The study presents a more comprehensive understanding of franchisees’ decision-making process when joining franchise chains by identifying the activities undertaken and criteria used to identify and evaluate franchise opportunities.

The Bed and Breakfast (B&B) enterprises generally lack sufficient human resources and time to conduct research on important social media marketing factors for visitors’ satisfaction and visitors’ intentions. Therefore, this study aims to provide crucial social media marketing and factors and service quality elements for improving customer satisfaction and customer loyalty in B&B sectors. This study also provides some recommendations for attracting more visitors and increasing customer satisfaction and customer loyalty through social media.

First, social media marketing factors and service quality elements were identified through the systematic literature review. Then these identified factors and elements were used to design a survey questionnaire for collecting data. The research data included responses of 64 B&B enterprises and 625 customers. The collected data was analyzed by feature selection approaches including Decision Tree algorithm and Information Gain to identify the key factors for improving customer satisfaction and customer loyalty.

The findings of this study determined that featured choice is an important social media marketing factor, and assurance is the common service quality element for both B&B enterprises and their customers in terms of satisfaction and loyalty.

This study adds a value to the growing literature on customer satisfaction and loyalty in B&B sectors by exploring key social media marketing factors and service quality elements. The study reveals several implications for theories and practices. The findings hopefully help B&B enterprises better social media marketing with less workforce and budget.

This research examines micro‐enterprises pursuing gradual growth. The research findings and implications are provided in two parts. Part 1 was presented in Volume 6, Number 4 of the Journal of Small Business and Enterprise Development (JSBED) (Perren, 2000). It developed an empirically verified framework that explains how growth was influenced by a myriad interacting factors; this led to a discussion of the policy implications of the framework. Part 2 explores the managerial implications of the framework. A diagnostic toolkit is systematically developed to encourage micro‐enterprise owner‐managers and advisers to explore the influences on the interim growth drivers identified in part 1. It is hoped this will help them to highlight ways of “compensating” deficits in particular factors and to think creatively about growth opportunities. The audience has changed from academics and policy‐makers to owner‐managers, so the diagnostic toolkit avoids technical language and employs a Socratic questioning approach to encourage free‐thinking and self‐analysis.

To develop a structural model based on Interpretive Structural Modelling (ISM) approach to analyse the barriers to integration of Lean with Industry 4.0.

Integrated lean and I4.0 is essential for optimising customer value, rapid product design and redesign to comply with customer demand on time. Also, manufacturing processes to be made more flexible, intelligent and agile. In this context, integrated lean and Industry 4.0 barriers were identified and an ISM approach is employed to identify hierarchical structure of barriers and analysed.

The result obtained reflects that barriers “increasing competitive pressure”, “lack of long-term vision”, “lack of management support”, “lack of capital fund” are found to be the important barriers that affect the integration of lean and I4.0.

In the present study, 16 barriers are analysed. In future, additional barriers could be included.

The driving and dependence power of barriers were analysed from ISM model and it provided guidance for practitioners to concentrate on barriers for integrating lean and I4.0.

The idea of developing structural model for analysis of barriers to integration of lean with I4.0 is the original contribution.

A new generation of advanced, supersonic, fighter aircraft windshields and canopies is taking shape at the Sylmar, California facility of Sierracin Corporation under the impetus of an Air Force search for the ideal transparencies for current and future US fighters.

The purpose of this paper is to explore and analyse the critical success factors (CSFs) of humanitarian supply chains in mitigating the impact of cyclones in the Indian context using the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach.

The selection of CSFs of humanitarian supply chains has been done through several secondary sources and discussion with 12 disaster experts. Thereafter, DEMATEL, an expert judgement-based technique, has been used for selecting, building and analysing a structural model that involves causal relationships between the set of identified CSFs. Furthermore, to accommodate the vagueness involved in human judgement, fuzzy logic is incorporated with the DEMATEL.

Based on a literature survey and expert judgement, total 16 CSFs of humanitarian supply chains have been segmented into cause and effect groups based upon their relative influencing scores. The analysis shows that the out of 16 CSFs, ten CSFs have been categorised into cause group CSFs and six as the effect group CSFs.

The findings of this study will help disaster management institutions, humanitarian agencies, logisticians, NGOs and cyclone-prone countries to improve the critical ingredients in designing and executing an effective cyclone response operation.

In this study, fuzzy DEMATEL has been applied to identify and analyse the CSFs of humanitarian supply chains for the cyclone disaster response in the Indian context, which is a novel contribution widening the existing knowledge in humanitarian relief domain.

Sizing functions are crucial inputs for unstructured mesh generation since they determine the element distributions of resulting meshes to a large extent. Meanwhile, automating the procedure of creating a sizing function is a prerequisite to set up a fully automatic mesh generation pipeline. In this paper, an automatic algorithm is proposed to create a high-quality sizing function for an unstructured surface and volume mesh generation by using a triangular mesh as the background mesh.

A practically efficient and effective solution is developed by using local operators carefully to re-mesh the tessellation of the input Computer Aided Design (CAD) models. A nonlinear programming (NLP) problem has been formulated to limit the gradient of the sizing function, while in this study, the object function of this NLP is replaced by an analytical equation that predicts the number of elements. For the query of the sizing value, an improved algorithm is developed by using the axis-aligned bounding box (AABB) tree structure.

The local operations of re-meshing could effectively and efficiently resolve the banding issue caused by using the default tessellation of the model to define a sizing function. Experiments show that the solution of the revised NLP, in most cases, could provide a better solution at the lower cost of computational time. With the help of the AABB tree, the sizing function defined at a surface background mesh can be also used as the input of volume mesh generation.

Theoretical analysis reveals that the construction of the initial sizing function could be reduced to the solution of an optimization problem. The definitions of the banding elements and surface proximity are also given. Under the guidance of this theoretical analysis, re-meshing and ray-casting technologies are well-designed to initial the sizing function. Smoothing with the revised NLP and querying by the AABB tree, the paper provides an automatic method to get a high-quality sizing function for both surface and volume mesh generation.

From last few decades, logistics management (LM) constitutes a global concern among organization’s supply chain (SC) to improve their business effectiveness. The purpose of this paper is to uncover and analyze the critical factors (CFs) related to the implementation of effective LM concept and benchmark the SC performance.

The most common (16) CFs were identified and selected through literature and use of the Delphi method. Subsequently, the selected most common CFs were analyzed to distinguish their causal relations using the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) technique under unclear surroundings. A case example of Indian Logistics Company is also discussed to reveal the practical applicability of the research.

Provision of the effective information communication and technological developments in the system and Management dedication, support and involvement CFs are found to have the top most influences in the effective implementation of LM. This paper also groups the CFs into cause and effect relationship which provides valuable insights for analyzing the factors in successful implementation of LM.

This work attempts to understand the different CFs, their relative position and the importance rating in the system, due to which, managers can differentiate the factor which greatly affects the concepts of implementing LM, and thus, improvements can be made accordingly.

First, this work offers 16 CFs to LM implementation from a SC scenario. Second, in the context of contributing to the theory, the combined Delphi and fuzzy DEMATEL-based model is provided that helps in managing the logistic related issues effectively.