The question of whether suicide bereavement is different from mourning after other types of deaths has important theoretical and clinical implications. Some recent literature reviews have argued that the differences may be minimal. In contrast, this article suggests that suicide bereavement is distinct in three significant ways: the thematic content of the grief, the social processes surrounding the survivor, and the impact suicide has on family systems. In addition, problems in the methodology used to compare different bereavement experiences are addressed. Some clinical implications of these conclusions, including the need for homogeneous support groups, psychoeducational services, and family and social network interventions are also discussed.

https://johnjordanphd.com/pdf/pub/Jordan_%20Is%20Suicide%20.pdf

Is suicide bereavement different? A reassessment of the literature.

Purpose – A key vision of tomorrow's industry is creating supply chains which collaboratively strive on enhancing the value to the end-consumer. The purpose of this paper is to introduce the food value chain analysis (FVCA) methodology for improving consumer focus in the agri-food sector based on the lean paradigm, value stream mapping and value chain analysis (Porter, 1985).

Design/methodology/approach – This contribution presents a case-study of a UK red meat supply chain explaining how the FVCA method enabled a team of researchers and practitioners to identify the misalignments of both product attributes and supply chain activities with the consumer needs.

Findings – This paper explains how the FVCA methodology potentially realigned the processes along the supply chain with the true consumer requirements and why the supply chain effectiveness was improved; this follows with a description of the subsequent efficiency gains from application of the FVCA methodology.

Originality/value – This paper further defines the demarcation between supply chain “effectiveness” and “efficiency”. This paper contributes to the debate on the importance of supply chain effectiveness by linking to consumer value at every stage of the supply chain.

Value chain analysis in consumer focus improvement: A case study of the UK red meat industry

The paper analyzes the evolution of container terminal productivity and efficiency of 20 terminals in 10 countries in Latin America and the Caribbean and Spain for the period 2005–2011. The inclusion of data from the demand growth period, and the subsequent reduction of demand and recovery, allows evaluating the impact and repercussion of the financial crisis on terminal productivity and efficiency. The aim of the empirical analysis in the paper is twofold: a) to document the harmonic mismatch in the evolution of port infra- and superstructure endowment, container demand in key Latin American and Caribbean container terminals and; b) to quantify the effect of the financial crisis and the posterior changing economic development on container port productivity applying non-parametric Data Envelopment Analysis (DEA). The panel data analysis allows for specifically identifying the effect of dynamic economic environments on productivity and efficiency on individual terminals.

The evolution of container terminal productivity and efficiency under changing economic environments

Data Envelopment Analysis (DEA) is an increasingly popular management tool. DEA is commonly used to evaluate the efficiency of a number of producers. A typical statistical approach is characterized as a central tendency approach and it evaluates producers relative to an average producer. In contrast, DEA compares each producer with only the "best" producers. By the way, in the DEA literature, a producer is usually referred to as a decision making unit or DMU. DEA is not always the right tool for a problem but is appropriate in certain cases.

with Data Envelopment Analysis

There is a widely shared perception that Management Information Systems (MIS) research has significantly improved in both quantity and quality over the past decade. Most MIS academics and practitioners have strong opinions about who the leading MIS researchers are and which institutions are on the cutting-edge with respect to MIS research. To a large extent, these opinions are subjective, based on impressions about specific MIS researchers, their work, and the institutions they represent. To complement the subjective judgment about the leading MIS researchers and institutions, this work has ranked the leading MIS publishers and institutions according to measurable objective criteria. It is the purpose of this study to assess the research productivity of MIS researchers and institutions in the leading MIS journals for the period 1991 through 1996 using measures-normal count, adjusted count, and productivity score-suggested in the previous studies (Lindsey, 1980; Jackson and Nath, 1989; Grover et al., 1992). In particular, this paper seeks to answer:

/pdf/an-assessment-of-individual-and-institutional-research-4yb5x8b11h.pdf

An Assessment of Individual and Institutional Research Productivity in MIS

Traditionally, raising the level of technology is considered the most effective way to improve productivity. Nevertheless, without the support of sound management systems, the contribution of technology to productivity is limited. In a sample of fifteen machinery firms, this paper calculates three indices for automation technology, production management, and productivity, respectively, to represent their levels of achievement. By using technology and management as the explanatory variables, a piecewise linear productivity frontier is constructed by applying a data envelopment analysis approach. At a given combination of the levels of technology and management, a firm may not be able to achieve the expected maximum productivity due to inefficient utilization of the input factors. One approach, the efficiency approach, for improving productivity which does not require the consumption of extra resources is to efficiently utilize the input factors. Another approach, the effectiveness approach, is to adjust the levels of technology and management toward the best combination to accomplish the highest productivity. Based on the productivity frontier constructed from the surveyed firms, the two approaches for improving productivity are discussed.

Productivity improvement: Efficiency approach vs effectiveness approach

Business units are always faced with intensifying pressure in a competitive economy. Increasing productivity is an effective solution for a firm to survive and prosper. The relative productivity in an industry has evolved into a significant determinant of the competitive position for a firm. This paper proposes a productivity diagnosis process for a firm on the basis of the productivity characters of an industry to gain an insight into the firm's relative productivity and to find the shortcomings in its management of resources. Firstly, productivity structure is determined. Pattern recognition technologies, namely fuzzy clustering and fuzzy classification, are then employed. After fuzzily clustering a training set according to three feature spaces, the productivity characters of the industry can be determined. A business unit can be diagnosed through fuzzily classifying its productivity features in a particular feature space and productivity indications can be furnished based on the associated productivity characters. As an illustration, data from 23 machinery firms in Taiwan are collected as a training set to analyze the productivity characters in each space, and two hypothetical firms are diagnosed.

Productivity diagnosis via fuzzy clustering and classification: An application to machinery industry

An effective way for improving productivity considered by most people is by raising the level of technology. However, without the support of sound management systems, the contribution of technology to productivity is limited. As an empirical verification, four major factors of automation technology are evaluated for fifteen machinery firms in Taiwan to constitute a composite index as an indicator of the achievement of technology. Similarly, eighteen subjects concerning production management are evaluated to result in an index for management. To construct a productivity frontier as a function of the two indices, a total factor productivity is also calculated. The productivity frontier shows the maximal attainable productivity at different levels of technology and management. It is worthwhile to note that, in the sampled firms, management presents a much stronger effect on productivity than technology does. With an isoquant analysis, a firm is able to derive a strategy to improve productivity takin...

Improving productivity via technology and management

Appropriate job selection and career planning largely determine successful career development Investigates some aspects of career development in industrial management from a sample survey conducted over the manufacturing industries in Taiwan Derives regression lines reflecting the salary changes at different ages for different education levels and education majors Develops a career path chart displaying the position migration trend To assist ambitious individuals seeking industrial management as a career, discusses desired qualifications including education level, educational discipline and educational training

Career paths in industrial management: a survey of Taiwan’s manufacturing industries

SUMMARY CAD, CAM, FMS, robotics, etc. have been considered by many manufacturing firms as promising technologies for achieving competitive advantage. Accompanied with the development of the delicate factory system, the role of scientific management becomes increasingly important. To understand the position of a firm vis-a-vis its competitors, this paper evaluates the levels of technology and management of 15 machinery firms by constructing two composite indices. The technology index is constructed from the indicators of equipment, employee, control level, and technological capability, whereas the management index is constructed from 18 subjects of manufacturing management. Through a cluster analysis, three production patterns, namely, tradition, over-engineering, and management-leader, are distinguished based on the levels of technology and management. The productivities of the surveyed firms reveal that management-leader is the group with stronger competitiveness that the machinery firms should consider ...

Shyanjaw Kuo

Papers

Productivity improvement: Efficiency approach vs effectiveness approach

Productivity diagnosis via fuzzy clustering and classification: An application to machinery industry

Improving productivity via technology and management

Career paths in industrial management: a survey of Taiwan’s manufacturing industries

Production pattern of machinery firms: Viewpoints of technology and management