Doing Well by Doing Right

Labor turnover has been defined as a phenomenon which serves to reflect the degree of stagnation or instability in the labor market. Whenever the rate of labor turnover is high, vis-a-vis, no expansion, excess movement and waste are said to result. On the other hand, when the labor turnover rate is low or equal to zero, the labor market is defined as in a state of stagnation. In either case (extremely high levels of turnover or extremely low levels of turnover) waste and under utilization of manpower are said to result. The impact from either too much or too little labor movement is felt to be dependent upon the size and maturity of the labor market. Moreover, the general level and diversity of skill on the part of labor market participants, may act to enhance or abate the effect of job turnover. This study was undertaken to investigate labor turnover in a selected area of eastern Arkansas. The area was chosen because of the large number of displaced agricultural workers who were in the employ of small industrial establishments which had recently moved into the area. It was hoped that the study would provide information which would be of value in solving problems related to the process of rural industrialization. Also, it was felt that information could be gained on problems faced by displaced agricultural workers as they transfer out of agricultural occupations. The purpose of this study, stated in a more specific sense, was to provide answers to some basic questions. They were: (1) Are the labor turnover rates among the firms high enough or low enough to warrant concern? (2) If labor turnover does, in fact, persist at problem levels, are there circumventable costs which arise in direct relationship with labor turnover? (3) Are there specific variables which tend to enhance or have a directional relationship with job turnover and cost? (4) What is the nature and extent of the relationship between labor turnover and specified variables? Data utilized in the study came from a number of sources including: (1) a survey schedule, (2) personnel and payroll records of firms, (3) area manpower studies, and (4) United States Census Bureau. The data were analyzed through the employ of some basic statistical models adapted for use in this study. A form of the stepwise regression routine (Goodnight's Maximum R2 Improvement Technique) was used to investigate relationship's between dependent variables and sets of independent variables. The analysis of variance linear model was also adapted for use in the study. The simple linear form of the ANOVA technique was used in determining if the firms were of the same population when considerations were given to criteria such as: (1) the level of turnover, (2) the cost of turnover and (3) the rates of quits, discharge, layoff, recall, new hire, flux and replacement. A version of the three factor factorial model (with nested classifications) was used to investigate the effects of specified factors on the rate of labor turnover in the panel firms. This study was limited by a number of factors. Thus, the conclusions and generalizations are limited. The scope of the inquiry was limited to: (1) only those firms of the eastern Arkansas area which employed displaced agricultural workers and hired more than fifty factory employees, (2) a period of three years - January 1970 through December 1972, (3) a six county section of the East Planning, and Development District of eastern Arkansas, and (4) investigation of the extent, costs, and causes of labor turnover in the panel firms. By virtue of the process used in selecting the firms and in selecting the study area, this investigation was a case study in nature. The findings on the general extent of labor turnover were supportive of the initial hypothesis that depressed wage regions are subject to high rates of "job switching." In most of the panel firms the rate of labor turnover was highly variable and reached extreme periodic highs and lows. Estimates made on monthly, quarterly and yearly bases were all high relative to representative United States manufacturing firms during the same period. Fluctuations in the rate of job turnover for all firms were sharp and typified a situation of instability in the labor market. In 1970 the mean level of employee turnover reached a within year high of 18 per 100 workers and fell to a low of 2.2 per 100 workers at one point. Separate observations on individual firms show that some firms sustained even more severe fluctuations, although most firms experienced declining rates over the 1970-72 period. Job switching was not identified as a market-wide-time-specific phenomena as its presence was seldom of uniform and harmonic occurrence among firms over time. The high rate of labor turnover arose from a combination of voluntary quits, replacements, and a slightly expanded level of employment in the panel firms. From an aggregate perspective it appeared that turnover arose from a collection of individual worker decisions to switch from situations perculiar to each firm and from market phenomena which affected the firms in a dissimilar temporal manner. The costs of labor turnover were identified to have emerged in four basic categories: (1) recruitment cost, (2) selection and placement cost, (3) on-the-job cost, and (4) cost of separating the incumbent. The overall labor turnover bill was comprised of four major components. Their aggregate and per hire cost over the period were: Aggregate Per Hire Recruitment ........................ $ 25,727 $ 5 Selection and Placement ............ 603,645 124 On-the-Job Cost .................... 3,275,051 673 Cost of Separation................ 665,547 136 Total......................... $4,569,971 $939. While labor turnover cost was estimated at $939 per hire over the 1970-72 period, it varied over a range of from $819 to $1,094. Percent distribution of the aggregate cost of turnover among the four major categories was: less than one percent to recruitment, 13 percent to selection and placement, 72 percent to on-the-job cost, and 14 percent to separation. Shares of the total maintained by the above components remained relatively stable over the 36 month period. For all firms the relationship between labor turnover and cost was decidedly strong. The correlation between the rate of turnover and cost of turnover was highly significant. The relationships between the cost of turnover and the primary categories of worker movement were investigated. Voluntary quits were designated to have had the stronger relationships with labor turnover cost when consideration was extended to cover only the single most influential factor. Layoffs, new hires, recalls and discharges were found to have possessed a significant relationship with the cost of turnover. While voluntary quits and new hires, individually, were observed to have exerted strong influence on the rate of turnover and cost, the main brunt was felt when firms sustained high rates of new hire and voluntary quits in combination. The criteria selected for use in attempting to explain variance in the rate of turnover were wage level, experience required before granting wage increases, distance employees commuted, the level of female employment, firm size, industry type and expenditures for preventive practices. All factors were found to have had some effect upon the rate of turnover when all possible combined factor effects were considered. In a net-effect sense, the level of female employment and firm size were determined not to have weighed significantly upon the rate of turnover. It was concluded that labor turnover in the eastern Arkansas area, and areas of similar characteristics, represents a serious impediment to the efficient operation of the firms. To the extent that labor turnover leads to unnecessary cost and to instability in the labor market, it is felt that efforts to advance rural industrialization are subject to serious setbacks whenever turnover exists at chronically high levels.

This paper aims to study the collaborative replenishment issue in the prefabricated supply chain of electronic products. Firstly, it analyzes the current situation of the replenishment mechanism in the electronic product supply chain, reveals the limitations of the traditional replenishment mechanism, and emphasizes the importance of collaborative replenishment. Secondly, it studies the impact of supply chain collaborative management on replenishment, including the concept and principle of collaborative management, the application of collaborative management in replenishment, as well as the benefits and limitations brought by collaborative management. Then, it discusses the impact of demand forecasting on replenishment decisions, including demand forecasting methods and their applicability, the impact of prediction accuracy on replenishment efficiency, and the challenges of demand volatility to the replenishment plan. Finally, it proposes optimization and implementation suggestions for replenishment strategies, including the exploration of new replenishment modes, data-driven replenishment decisions, and the path and obstacles of cross-organizational collaborative replenishment. The results of this study can provide theoretical support and practical guidance for the replenishment management of the electronic product supply chain. They can also help promote enterprises to achieve sustainable development in the highly competitive market.

The re-design of supply chains for smoother, faster response has been the subject of much research and debate since the classic contribution by Jay Forrester (1961) over 30 years ago. Many of his ideas have since been subsumed within business process re-engineering (BPR) but this involves the 'how' as well as the 'why' of supply-chain management. The authors use a real-world electronic products supply chain as a case study in which it has proved feasible to model and simulate a number of BPR driven strategies undertaken to improve supply chain performance. The modelling and simulation techniques essentially follow a classical industrial dynamics format, although a greater than usual contribution was made via people contact and written documentation methods coupled with the exploitation of inhouse software. The improved demand amplification patterns predicted from the simulation model can be used for benchmarking purposes and for prioritising future improvement programmes by other supply chains.

A grey-layered ANP based decision support model for analyzing strategies of resilience in electronic supply chains

Supply chain digitalization: An integrated MCDM approach for inter-organizational information systems selection in an electronic supply chain

FOCUS | INDUSTRY 4.0 13 25/3 | International Union Rights | Mobile devices, sensors, screens, chips, and robots… do not fall out of the sky. Much of the debate on labour and Industry 4.0 has centred on the application of new technologies across the labour market. Somewhat less attention is paid to the production of these technologies – and still less their dependence on the extraction of certain raw materials. The electronics sector is increasingly linked to highly exploitative working conditions and practices, and significant risks of modern slavery in its supply chains. One recent report describes forced labour as the ‘backbone’ of global electronics manufacturing1. In respect of its raw material inputs, companies appear more or less indifferent to where and how these are sourced. In 2016, the Australian Behind the Barcode project ranked fifty-six electronics companies ‘on the strength of their labour rights management systems to mitigate the risk of forced labour, child labour and exploitation in the supply chain’2. One table in the report illustrates these companies’ scores at the point of raw material extraction: it is block red. Universally, the companies failed on questions of traceability, monitoring and labour standards. Not one company could guarantee a living wage, not one had a child labour policy, no collective bargaining agreement was recorded, and none reported that they based sourcing decisions on supplier labour conditions. Of the fifty-six, only one company achieves a ‘partial’ tick, for having at least a pilot labour grievance mechanism in operation in the extraction part of its supply line. The Raw Materials of a Revolution The mass expansion of technologies heralded under the title ‘Industry 4.0’ will clearly require a massive growth in mineral extraction. It is little surprise that the extraction needed for these technologies will take place in the Global South. According to some estimates, by 2035 demand for rare earths will increase three-fold, for lithium fourfold3. Cobalt demand will rise to more than twenty times its current rate, and copper more than forty-times. Others predict that global copper demand may grow by over 300% until 2050. The massive growth in industrial demand for the raw materials that new technologies will require is bound to have social and environmental costs. Does Industry 4.0 simply spell a new ‘resource curse’ for countries rich in these raw materials? What impact will the growth in demand have on labour conditions already prevailing in the supply chains of these goods? Discussions about ‘Industry 4.0’ could do well to heed the examples of the first industrial revolution. Industry 4.0 is deeply rooted in that revolution: the digital genealogy of machine code can be traced back to the Jacquard loom. Technology was central to Britain’s rapid industrialisation, and to the rise of cotton in textile production, replacing wool due to the advantages of newly mechanised cotton processing. By the middle of the 19th Century, cotton represented one tenth of all British capital investment and accounted for almost one half of British exports. A quarter of the British population was dependent on the cotton trade for their livelihoods4. This relatively arbitrary technological advance also contributed significantly to the economic ascendency of the United States. The ‘prototype machine industry’ massively increased the demand for raw cotton from planters in the Caribbean and the Americas. Imports to Britain grew eightfold between 1780 and 1800. Mechanised spinning therefore created ‘rising demand for raw cotton resulting in the extension of the slave plantation system’5. Questions about labour rights and Industry 4.0 should require us to think about how different workers’ rights are differently impacted, including in the electronics supply chain. In the first industrial revolution, technology had variable impacts on existing labour practices. The introduction of weaving machines into British textile factories dealt a deathblow to the guild system of skilled craft workers and the economic relations that went with it. On the cotton plantations however, the late eighteenth century invention of the cotton gin reduced the labour required to remove seeds, but this efficiency gain only provoked a massive expansion of US cotton planting and with it the intensification – rather than any reduction – of slave labour. And for its importers...

With the rapid development of the network economy, it is a marketing strategy to provide an extended warranty (EW) service. Considering the differences in the EW service providers and dominant enterprises, this paper proposes four kinds of decision-making models and aims to study decisions of the electronic commerce supply chain, including EW price, sales price, and service level of e-platform. Through comparative analysis and numerical analysis, this research shows that, among four decision-making models, the highest system profit can be achieved when the seller provides the EW service and the e-platform dominates the system. For electronic commerce supply chain enterprises, whether to dominate the system or to provide EW service, it is conducive to the increase of profits. When the e-platform provides the EW service, the conclusion is that who dominates the system is the one who gets more profit. However, when the seller provides the EW service, the conclusion is that who dominates the system is the one who gets less profit. When the EW service is offered by the dominating enterprise, service levels of the e-platform are lower.

IT resources and quality attributes: The impact on electronic green supply chain management implementation and performance

With the continuous development of e-commerce, it has become normal for the manufacturer to sell products and to collect used products through e-commerce platforms (platform for short). We consider an electronic closed-loop supply chain (E-CLSC) where we composed a manufacturer with remanufacturing capability and a platform that can provide logistics services. The purpose of this paper is to address whether the manufacturer should directly collect used products from the consumer under the platform. Specifically, we have developed four game models, namely model N (no collection), model M (the manufacturer collects), model E (the platform collects), and model T (the third-party collects) and derived the optimal pricing decisions, logistics service level, and collection rate for E-CLSC members. We found that remanufacturing used products is conducive to increasing the profits of the manufacturer and the platform as well as to increasing the utility of the consumer. Under the same conditions, for the manufacturer, the platform, and the consumer, the optimal choice is that the manufacturer directly collects the used products from the consumer. If the manufacturer is unable to establish an effective collection channel, he should consider outsourcing to a contractor and should consider the platform to be under the same conditions. Numerical examples are also given to verify the proposed results.

Many strategies have been developed to manage supply chain operations effectively. Vendor Managed Inventory (VMI) system is one of the prevalent strategic tools of the supply side logistics based on the electronic data exchange and business process automation among the suppliers and customers to enhance the competitive advantage. VMI is widely used in different industries including automotive sector. The VMI concept is a continuous replenishment program where suppliers are given access to demand and inventory level of customers and they are fully responsible for managing and replenishing the customer’s stock. VMI’s extension on customer satisfaction cannot be perceived sufficiently by decision-makers who are responsible to develop and invest in the customer-supplier relationship. This paper presents a path model using the method of Partial Least Squares (PLS) regression to give insight to decision-makers to understand effect of the VMI adoption on customer satisfaction. This paper investigates both determinants of relative factors of successful VMI adoption and the relationship in the supply chain with an empirical automotive industry case. The results show that the collaboration and coordination between customer and supplier and infrastructure of the information-sharing are the important dimensions to add value to the supply chain and to enhance customer satisfaction.

The globalized electronics supply chain relies on many untrusted entities to move components across the world. This, in turn, increases the threat of counterfeit integrated circuits (ICs) being inserted into the supply chain then installed into mission critical systems. A number of methods for detecting counterfeit ICs exist; however, applications of models to rapidly and non-destructively detect cloned ICs are lacking. Moreover, no trustworthy data storage and verification mechanism exists in the current supply chain that can provide identification and tracking of authentic and cloned ICs. In this work, we propose a novel framework to address these detection and tracking problems at each stage of the electronics supply chain. We leverage a consortium-style blockchain infrastructure to offer tamper-proof data enrollment and verification. We propose the algorithm and model for confidently identifying authentic and cloned ICs, and offer next stage tracking by verifying general and restricted datasets in the blockchain. The experimental result demonstrates how entities can verify and track the cloned chips with a given level of confidence in the presence of noise.

Providing high-quality service to all users is a difficult and inefficient strategy for e-commerce providers, especially when Web servers experience overload conditions that cause increased response time and request rejections, leading to user frustration and reduced revenue. In an e-commerce system, customer Web sessions have differing values for service providers. These tend to: give preference to customer Web sessions that are likely to bring more profit by providing better service quality. This paper proposes a reinforcement-learning based adaptive e-commerce system model that adapts the service quality level for different Web sessions within the customer’s navigation in order to maximize total profit. The e-commerce system is considered as an electronic supply chain which includes a network of basic e- providers used to supply e-commerce services for end customers. The learner agent noted as e-commerce supply chain manager (ECSCM) agent allocates a service quality level to the customer’s request based on his/her navigation pattern in the e-commerce Website and selects an optimized combination of service providers to respond to the customer’s request. To evaluate the proposed model, a multi agent framework composed of three agent types, the ECSCM agent, customer agent (buyer/browser) and service provider agent, is employed. Experimental results show that the proposed model improves total profits through cost reduction and revenue enhancement simultaneously and encourages customers to purchase from the Website through service quality adaptation.

The primary objective of closed-loop supply chains (CLSC) is to improve the maximum economic benefit from end-of-use products. Nevertheless, the literature within this stream of research advocates that closing the loop also helps to mitigate the undesirable environmental footprint of supply chains. Therefore, closed-loop supply chains are assumed to be sustainable supply chains almost by definition. In this paper we analyse if and when this assumption holds. We illustrate our findings based on the Electric and Electronic Equipment (EEE) supply chain. For all phases of the supply chain, i.e. manufacturing, usage, transportation and end-of-life activities, we assess the magnitude of the environmental impacts, based on a single environmental metric, namely the Cumulative Energy Demand (CED). Given the environmental hot-spots in the Electric and Electronic Equipment supply chain, we propose useful extensions for existing CLSC optimisation models to ensure that closed-loop supply chains are at the same time sustainable supply chains.

This article explores the convergence of digital innovation and its negative consequences (such as e-waste) with modern sustainability goals by looking at contracts. Specifically, it discusses the use of sustainability contract clauses (SCCs) in business contracts as an expression of corporate social responsibility and of self-regulation. It suggests that there is potential in promoting the use of sustainable obligations in the electronics supply chain (the generator of the fastest growing waste source). As little guidance exists on sustainable obligations, this article discusses the possibility of establishing a new soft law instrument that could tackle some of the described legal challenges in the current use of SCCs. In doing so, it reflects on the possible issues of the proposed instrument.

Advances in information technology (IT) improve functionality for major nonprofit organizations. Due to increased expectations, service needs and peer competition, nonprofits must prepare to incorporate IT-related resources such as emerging technology planning, web- based collaborative processes and constrained resource planning to obtain technological innovation and higher performance. The effective use of constrained resource management is crucial for the success of nonprofits. Although nonprofit organizations are familiar with common IT resources and applications, wide application of new methods and technology is required to build inter-dependent information resources and real-time decision making capacity. Nonprofit resource planning such as tracking inventory level, planning replenishment, and receiving continuous information updates can be measured through enterprise resource planning (ERP) and electronic supply chain (e-SC) management. IT implementation of ERP and e-SC in nonprofits contribute to improve collaboration among donors, partner organizations, governmental agencies, staff members, volunteers, local experts, clients and recipients. This article addresses critical IT procedures and emerging IT practices to improve nonprofit performance. The overall goal is to focus IT implementation in nonprofits to develop road maps to guide organization pathways, track progress and measure success for public services.