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This chapter reports estimates of consumers’ preferences for plans to improve food safety.

The plans are distinguished based on whether they address the ex ante risk of food borne illness or the ex post effects of the illness. They are also distinguished based on whether they focus on a public good – reducing risk of illness for all consumers or allowing individual households to reduce their private risks of contracting a food borne pathogen.

Based on a National Survey conducted in 2007 using the Knowledge Network internet panel, our findings indicate consumers favor ex ante risk reductions and are willing to pay approximately $250 annually to reduce the risk of food borne illness. Moreover, they prefer private to public approaches and would not support efforts to reduce the severity of cases of illness over risk reductions.

This study is the first research that allows a comparison of survey respondents’ choices between public and private mechanisms for ex ante risk reductions.

Presented is a path analysis of causal connections between several open‐plan attributes and discrete effective facilities space management aspects of commercial offices in Sydney. The aim is to use quantitative estimates to demonstrate in structural equations the effect coefficients of the complex connections between selected open‐plan and effective facilities space management variables. Over one hundred open‐plan offices in the Sydney CBD were examined. Some open‐plan attributes were found to have direct impacts on several effective facilities space management variables, while others exhibited indirect effects through management control aspects. In most cases, management control reduced the effect coefficients. This paper concludes that, with dedicated management control, the impact of open‐plan on facilities space management may be less extensive. The implication of this result is for re‐engineering of work environments to consider aspects of management that invariably moderates and/or intervenes in the relationship of space, people and work process.

This paper aims to address the supplier selection problem based on a developed framework capturing the essence of the supply chain operations reference (SCOR) model, sustainability and providing services to customers. Specifically, the authors consider planning, manufacturing, delivery, sustainability and customer service attributes to evaluate and select suppliers.

Relevant literature is reviewed, a framework capturing the essence of major supply chain functions was developed and suitable measurement attributes were identified. An integrated fuzzy analytic hierarchy process and fuzzy technique for order performance by similarity to ideal solution method are employed to obtain the final ranking of the attributes and suppliers. The proposed methodology is illustrated through a real case of an Indian automobile company.

The authors observed that planning, manufacturing, customer service, sustainability and delivery are preferred in decreasing order to select component suppliers for an automotive company. The impact of suppliers on planning and manufacturing is most important to consider while assessing suppliers. Interestingly, concerns about sustainability and delivery are the least cared factors when selecting suppliers. The top five criteria contain measures of operational efficiency rather than purchasing cost.

This paper proposes and demonstrates a supplier selection framework harmonizing supply chain functions of the SCOR model, sustainability and customers service that adds a valuable wing to literature that expounds on the connection of purchasing strategy to corporate strategy. A case study in an automotive company throws unique and valuable managerial implications for purchasing and supply chain performance.

This study investigates the repetitive mixed sampling (MRS) plan based on the Cpk index that was proposed by Aslam et al. (2013a). They were the first to study the MRS plan, but they did not pay attention to the fact that submitting to the variable inspection a sample that was first submitted to the attribute inspection, truncates the X observations. In addition, they did not work with an accurate expression to calculate the probabilities of the Cpk statistic.

The authors presented the results based on their original sampling plan through Monte Carlo simulation and defined the theoretical results of their plan when the sample submitted to the variable inspection is no longer the same one submitted to the attribute inspection.

The β risks of the optimum sampling plans presented by Aslam et al. (2013a) are pretty high, exceeding 46%, on average – this same problem was also observed in Saminathan and Mahalingam (2018), Balamurali (2020) and Balamurali et al. (2020), where the β risks of their proposed sampling plans are yet higher.

In terms of originality, the authors can declare the following. It is not a big deal to propose new sampling plans, if one does not know how to obtain their properties. The miscalculations of the sampling plans risks are dangerous; imagine the situation where the acceptance of bad lots exceeds 50% just because the sampling plan was incorrectly designed. Yes, it is a big deal to warn that this type of problem is arising in a growing number of papers. The authors of this study are the pioneers to discover that many studies focusing on the sampling plans need to be urgently revised.

The purpose of this paper is to propose a new mixed repetitive group sampling (RGS) plan based on the process capability index, C_pk, where the quality characteristics of interest follow the normal distribution with unknown mean and unknown variance. Tables are constructed to determine the optimal parameters for practical applications for both symmetric and asymmetric fraction non-conforming cases. The advantages of this proposed mixed sampling plan are also discussed. The proposed sampling plan is also compared with other existing sampling plans.

In order to determine the optimal parameters of the proposed mixed RGS plan based on C_pk, the authors constructed tables for various combinations of acceptable and limiting quality levels (LQLs). For constructing tables, the authors followed the approach of two points on the operating characteristic (OC) curve. The optimal problem is formulated as a non-linear programming where the objective function to be minimized is the average sample number (ASN) and the constraints are related to lot acceptance probabilities at acceptable quality level and LQL under the OC curve.

The proposed mixed RGS plan will be a new addition to the literature of acceptance sampling. It is shown that the proposed mixed plan involves minimum ASN with desired protection to both producers and consumers compared to other existing sampling plans. The practical application of the proposed mixed sampling plan is also explained with an illustrative real-time example.

In this paper, the authors propose a new mixed RGS plan based on the process capability index C_pk, where the quality characteristic of interest follows the normal distribution with unknown mean and unknown variance. Tables are constructed to determine the optimal parameters for practical applications. The proposed mixed sampling plan can be used in all production industries. This kind of mixed RGS plan is not available in the literature.

The purpose of this paper is to measure and map the potential transportation network impedance to last-mile delivery (LMD) using spatial measures representing attributes of road network and planning controls.

The transport network impedance is estimated as the potential hindrance to LMD as imposed by the characteristics of the built and regulatory environment. A matrix of key transport and planning measures are generated and overlaid in geographical information systems to compute and visualise the levels of transportation network impedance to LMD using a composite indexing method.

The mapped outputs reveal significant spatial variation in transportation network impedance to LMD across different part of the study area. Significant differences were detected along the road segments that connect key industrial hubs or activity centres especially along tram routes and freight corridors, connecting the Port of Melbourne and logistic hub with the airport and the Western Ring Road.

The use of static measures of transport and urban planning restricts the robustness of the impedance index, which can be enhanced through better integration of dynamic and real-time movements of business-to-business LMD of goods. Spatial approach is valuable for broader urban planning at a metropolitan or council level; however, its use is somewhat limited in assisting the daily operational planning and logistics decision making in terms of dynamic routing and vehicle scheduling.

The built and regulatory environment contributes to the severity of LMD problem in urban areas. The use of land use controls as instruments to increase city compactness in strategic nodes/hubs is more likely to deter the movement of urban freight. The mapped outputs would help urban planners and logisticians in mitigating the potential delay in last-mile deliveries through devising localised strategies such as dedicated freight corridors or time-bound deliveries in congested areas of road network.

This is the first study that measured the potential transport network impedance to LMD and improved understanding of the complex interactions between urban planning measures and LMD. Micro-scale mapping of transportation network impedance at the street level adds an innovative urban planning dimension to research in the growing field of city logistics.

The aim of the paper is to identify the key factors that affect Guinean family business (FB) succession planning. The study also evaluates the impact of these factors on the succession planning process to ensure business continuity.

This descriptive quantitative research is based on a survey of 383 family businesses FBs in Conakry, the capital city of Guinea. The structural equation model (SEM) was used to analyze and validate the model featuring factors that influence family business FB succession planning (FBSP). The Theory of Stewardess and the Theory of FB Rivalry have been employed in the study.

While the incumbent attributes, firm attributes, and estate tax were revealed to have no significant influence on succession planning, the successor attributes and the family relationship significantly affected succession planning. Besides, undesirable domestic relationships among children of different mothers from polygamous families had an indirect impact on business succession planning.

The limitations of the study include the population of the FBs being restricted only to those located in Conakry, the capital city. The study did not consider other regions and cities of Guinea. Besides, the grouping of attributes or characteristics was problematic, and studying each attribute separately as an independent variable would be much better. Finally, the limited literature and available data on Guinean FBs in general and succession planning generalize the findings to be done cautiously. Therefore, more studies are needed on FB succession in the country to further confirm these findings.

The study may help ensure social solidarity based on the findings of factors associated to polygamous families in relation to businesses.

Few studies have been done on FBs in Conakry. Besides, putting attributes or characteristics into categories has been presented. Moreover, there is inadequate relevant literature and data on Guinean FBSP. Considering these limitations, the generalization of the findings should be done with caution. Therefore, this study touched on the issue of family business succession in Guinea which substantiates the findings.

The purpose of this paper is to present the single sampling attribute plan for given acceptance quality level (AQL) and limiting quality level (LQL) involving minimum sum of risks using weighted Poisson distribution.

For the given AQL and LQL, sum of producer's and consumer's risks have been attained. Based on weighted Poisson distribution, the sum of these risks has been arrived at, along with the acceptance number and the rejection number. Also, the operating characteristic function for the single sampling attribute sampling plan, using weighted Poisson distribution, has been derived.

In the final inspection, the producer and the consumer represent the same party. So, the sum these two risks should be minimized. In this paper, the sum of risks has been tabulated using weighted Poisson distribution for different operating ratios. These tabulated values are comparatively less than the sum of risks derived using Poisson distribution.

The sampling plan presented in this paper is particularly useful for testing the quality of finished products in shop floor situations.

This purpose of this paper is to present an optimization‐based approach to support the design of attribute sampling plans for lot acceptance purposes, with the fraction of non‐conforming items being modeled by a Poisson probability distribution function.

The paper approach stands upon the minimization of the error of the probability of acceptance equalities in the controlled points of the operating curve (OC) with respect to sample size and acceptance number. It was applied to simple and double sampling plans, including several combinations of quality levels required by the producer and the consumer. Formulation of the design of acceptance sampling plans as an optimization problem, having as a goal the minimization of the squared error at the controlled points of the OC curve, and its subsequent solution employing GAMS.

The results are in strong agreement with acceptance sampling plans available in the open literature. The papers approach in some scenarios outperforms classical sampling plans and allows one to identify the lack of feasible solutions.

An optimization‐based approach to support the design of acceptance sampling plans for attributes was conceived and tested. It allows for a general treatment of these problems, including the identification of a lack of feasible solutions, as well as making possible the determination of feasible alternatives by relaxing some model constraints.

Presents a repetitive group sampling plan for three‐attribute classes where items are classified into three categories, namely good, marginal and bad. Derives various performance characteristics of interest to quality control engineers and plan designers through the approach of the Graphic Evaluation and Review Technique (GERT). In order to facilitate the operation and construction of the plan, tabulates Poisson unity values for a useful subset of the proposed plan.