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In 1989, approximately one third of Canadians over 15 years of age were cigarette smokers. Studies by the Royal College of Physicians of London and the US Surgeon General have clearly demonstrated the negative impact of smoking on health and have established smoking as a risk factor for cardiovascular disease, cancer and respiratory problems. It has been estimated that at least 38 000 Canadians die each year from smoking-related diseases. There are many approaches to combat tobacco consumption which include education, smoking cessation programs and legislation. Between 1980 and 1990, Canada imposed heavy taxation on tobacco products that resulted in a 35% decrease in tobacco consumption by the adult population and a 62% decrease in consumption by the teenage population. However, in the past two years smuggling has forced federal and provincial governments to reduce these high taxes on tobacco products. It has been estimated that the recent tax cuts will increase the number of smokers by approximately 800 000. Therefore, a new taxation policy should be introduced which differs from the previous tax in some key aspects. Any new tax increase should be moderate to help avoid the problem of tobacco smuggling and a portion of the tax should directed to fund smoking cessation programs.

PurposeThe purpose of this paper is to investigate the direct and interaction effects of shelf space, case pack quantity, and consumer demand on shelf stockouts, i.e. stockouts at the shelf level when inventory is available in the backroom of a retail store.Design/methodology/approachThis study uses discrete‐event simulation based on data collected from the ready‐to‐eat breakfast cereal category with multiple stockkeeping units (SKUs) to model a retail supply chain consisting of a supplier, a retailer, and consumers.FindingsThe results indicate that shelf space and case pack quantity have direct effects on shelf stockouts. Furthermore, evidence is found for interactions among shelf space, case pack quantity and consumer demand. Though many retailers adopt simple heuristics for shelf space allocation, such as a multiple of case pack quantity, this study suggests that such heuristics tend to over‐ or underestimate shelf space requirements when consumer demand is ignored.Originality/valueThis study suggests that managers should allocate shelf space for SKUs on the basis of not only case pack quantity but also consumer demand.

PurposeWhereas inventory theory traditionally assumes the periodic review inventory model (R, T), with an order‐up‐to level R, has a random demand and lead time coupled with a deterministic review interval T, firms often deviate from a strict adherence to a fixed review interval when they attempt to capture transportation scale efficiencies. Employing this policy introduces additional supply chain variability. This paper aims to provide an expression for the standard deviation of demand during the protection period, important in setting safety stock, as well as an expression for the amount of order variance amplification induced by a stochastic review interval.Design/methodology/approachAnalytical modeling is used to develop the expression for the standard deviation of demand during the protection period as well as the calculation for the amount of order variance amplification induced by a stochastic review interval.FindingsIn terms of the variance of demand over the protection period, a stochastic review interval has a similar effect to that of a stochastic lead time, but its impact on demand variance amplification within the supply chain differs fundamentally. Specifically, a stochastic review interval creates an order batching bullwhip effect not identified in existing literature.Research limitations/implicationsThis study offers an expression for the standard deviation of demand during the protection period when stochastic review intervals are employed. The expression can be used to more effectively set safety stock. The paper also offers an expression for the order variance amplification induced by a stochastic review interval.Practical implicationsThe study offers suggestions for retailers and suppliers regarding when the use of a stochastic review interval is effective in terms of cost efficiencies.Originality/valueWhile the existence and effect of lead time variability is well‐established in the literature, traditional approaches the periodic review inventory model ignore the stochastic nature of review interval. This paper highlights the use of stochastic review intervals as a contributing factor to the bullwhip effect.

PurposeThe purpose of this study is to investigate the impact of a key logistics and distribution variable, case pack quantity, on a consumer packaged goods (CPG) manufacturing firm's performance. The paper builds theory with respect to case pack quantity's dichotomous impact on the retail shelf replenishment process and subsequent impact on market share depending on product rate‐of‐sale (ROS).Design/methodology/approachThe study empirically tests the case pack quantity phenomenon using monthly in‐store data collected over a two year time period, market share data and data provided by a leading US CPG manufacturer in the ready‐to‐eat cereal category. Regression analysis is used to determine if case pack quantity significantly impacts firm market share.FindingsAccording to compelling theoretical and empirical evidence, the number of units per retail shipping container (case pack quantity) has a significant impact on retail market share. The evidence indicates that the effect of case pack quantity on market share depends upon the ROS of a given stock‐keeping unit (SKU). For faster selling SKUs, larger case packs should increase market share. For slower selling SKUs, larger case pack quantities reduce market share because of additional stockouts at the retail level, resulting from execution problems caused by the larger case pack quantities.Practical implicationsGiven the study's findings, CPG manufacturing firms must align case pack quantities with SKU ROS to positively affect the shelf replenishment process.Originality/valueThe paper demonstrates that case pack quality has a significant impact on retail market share.

Few studies have examined predictors of hospital readmission among high-using patients enrolled in a behaviorally oriented intensive care management program. The purpose of this case control study was to describe risk factors and the effectiveness of a complex care management program for hospital readmission among vulnerable patients at a large academic medical center. One hundred sixty-three patients enrolled in the University of Michigan Complex Care Management Program (UM CCMP) were hospitalized between January 2014 and March 2015. Sixty were readmitted within 30 days of discharge. Among all patients, the mean age was 51.1 years, 38.7% were non-White, 81.5% had Medicaid and/or Medicare, 50.3% were without stable housing, and 27.6% had significant psychiatric illnesses. Although mostly not statistically significant, multivariable risk of readmission was increased by having twice the mean number of hospitalizations in the last 6 months (odds ratio [OR] = 1.44, 95% CI [1.00, 2.06]), having chronic pain on a scheduled narcotic (OR = 1.49, 95% CI [0.67, 3.35]), and going to a primary care physician within 30 days of discharge (OR = 1.35, 95% CI [0.63, 2.89]). Risk was decreased by going to a specialist (OR = 0.54, 95% CI [0.23, 1.27]) and receiving moderate-intensity CCMP intervention (OR = 0.48, 95% CI [0.20, 1.19]). Among hospitalized high-using patients enrolled in the UM intensive care management program, readmission is likely significantly influenced by medical, behavioral, and social challenges. Care management appears most effective in preventing readmission among patients with mid- rather than high- or low-level needs. These findings at a single program should be explored in further, larger studies.

ABSTRACTAs the world's population continues to urbanize, providing efficient and effective logistics service to customers in urban areas has become an increasingly important, but difficult task. Recent vehicle routing studies suggest that logistics planners face numerous difficulties during decision‐making due to certain complexities associated with the urban environment, but to date, specific challenges have remained unidentified. Using a multiple case study methodology, this research examines several environmental characteristics that influence vehicle routing decisions across eight U.S. urban centers, and contrasts decisions firms make when creating solutions to address these factors. Cross‐case synthesis uncovered patterns connecting specific environmental characteristics with variations on traditional vehicle routing decisions. Results allow us to construct a theoretical framework and propositions to guide managers when tailoring urban logistics strategies to urban environments having different combinations of structural characteristics.

Purpose
– The purpose of this paper is to: first, provide a systematic review of the drivers of retail on-shelf availability (OSA) that have been scrutinized in the literature; second, identify areas where further scrutiny is needed; and third, critically reflect on current conceptualizations of OSA and suggest alternative perspectives that may help guide future investigations.


Design/methodology/approach
– A systematic approach is adopted wherein nine leading journals in logistics, supply chain management, operations management, and retailing are systematically scanned for articles discussing OSA drivers. The respective journals' websites are used as the primary platform for scanning, with Google Scholar serving as a secondary platform for completeness. Journal articles are carefully read and their respective relevance assessed. A final set of 73 articles is retained and thoroughly reviewed for the purpose of this research. The systematic nature of the review minimizes researcher bias, ensures reasonable completeness, maximizes reliability, and enables replicability.


Findings
– Five categories of drivers of OSA are identified. The first four – i.e., operational, behavioral, managerial, and coordination drivers – stem from failures at the planning or execution stages of retail operations. The fifth category – systemic drivers – encompasses contingency factors that amplify the effect of supply chain failures on OSA. The review also indicates that most non-systemic OOS could be traced back to incentive misalignments within and across supply chain partners.


Originality/value
– This research consolidates past findings on the drivers of OSA and provides valuable insights as to areas where further research may be needed. It also offers forward-looking perspectives that could help advance research on the drivers of OSA. For example, the authors invite the research community to revisit the pervasive underlying assumption that OSA is an absolute imperative and question the unidirectional relationship that higher OSA is necessarily better. The authors initiate an open dialogue to approach OSA as a service-level parameter, rather than a maximizable outcome, as indicated by inventory theory.

Purpose– The accurate measurement of demand variability amplification across different nodes in the supply chain, or "bullwhip effect," is critical for firms to achieve more efficient inventory, production, and ordering planning processes. Building on recent analytical research that suggests that data aggregation tends to mask the bullwhip effect in the retail industry, the purpose of this paper is to empirically investigate whether different patterns of data aggregation influence its measurement.Design/methodology/approach– Utilizing weekly, product-level order and sales data from three product categories of a consumer packaged goods manufacturer, the study uses hierarchical linear modeling to empirically test the effects of data aggregation on different measures of bullwhip.Findings– The authors findings lend strong support to the masking effect of aggregating sales and order data along product-location and temporal dimensions, as well as the dampening effect of seasonality on the measurement of the bullwhip effect.Research limitations/implications– These findings indicate that inconsistencies found in the literature may be due to measurement aggregation and statistical techniques, both of which should be applied with care by academics and practitioners in order to preserve the fidelity of their analyses.Originality/value– Using product-weekly level data that cover both seasonal and non-seasonal demand, this study is the first, to the author's knowledge, to systematically aggregate data up to category and monthly levels to empirically examine the impact of data aggregation and seasonality on bullwhip measurement.

Cognizant of the disappointing health status effects of home care in past studies, the authors argue that home care (homemaker, chore, day care, and other personal care services) is ill equipped to alter health status but could alter the way in which patients, family, and physicians respond to health status changes. If it does this, it should be effective in preventing some of certain types of hospitalizations: those for death, nursing home placement, and evaluation. This study, which reanalyzes the National Channeling Demonstration Project data set to focus on these three most promising outcome effects of home care found that it did not prevent these types of potentially avoidable hospitalizations. Indeed, there is little evidence that such targeted preventive efforts took place. This may suggest that the objective function of home care should be redefined to focus on altering responses to health status change rather than on altering health status.

Although evidence of effectiveness is limited, care management based outside primary care practices or hospitals is receiving increased attention. The University of Michigan (UM) Complex Care Management Program (CCMP) provides care management for uninsured and underinsured, high-utilizing patients in multiple primary care practices. To inform development of optimal care management models, we describe the CCMP model and characteristics and health care utilization patterns of its patients. Of a consecutive series of 49 patients enrolled at CCMP in 2011, the mean (SD) age was 48 (±14); 23 (47%) were women; and 29 (59%) were White. Twenty-eight (57%) had two or more chronic medical conditions, 39 (80%) had one or more psychiatric condition, 28 (57%) had a substance abuse disorder, and 11 (22%) were homeless. Through phone, e-mail, and face-to-face contact with patients and primary care providers (PCPs), care managers coordinated health and social services and facilitated access to medical and mental health care. Patients had a mean (SD) number of hospitalizations and emergency room (ER) visits in 6 months prior to enrollment of 2.2 (2.5) and 4.2 (4.3), respectively, with a nonstatistically significant decrease in hospitalizations, hospital days, and emergency room visits in 6 months following enrollment in CCMP. Centralized care management support for primary care practices engages high-utilizing patients with complex medical and behavioral conditions in care management that would be difficult to provide through individual practices and may decrease health care utilization by these patients.

PurposeDiscussions about the managerial relevance of scholarly research have been taking place for decades and the topic continues to be a source of debate in a number of business disciplines. The purpose of this paper is to make an initial attempt to empirically assess the relevance of supply chain management research.Design/methodology/approachQualitative methods were utilized to provide some initial evidence that can help validate or refute assumptions about perceived relevance in contemporary supply chain management research.FindingsFindings of this research indicate that the most impactful supply chain management issues for managers are internal supply chain organizational structure, communication and information exchange, information technology, forecasting and sales and operations planning, and strategic leadership. Some of these managerial issues appear to be well aligned with recent research trends, but other issues are not frequently researched.Research limitations/implicationsFuture research opportunities are identified based on managerial feedback. Results of this study also suggest that a broader view of supply chain management may be appropriate if researchers want to be managerially relevant.Practical implicationsThis research potentially highlights opportunities for firms to gain a competitive advantage via their approach to supply chain management.Originality/valueThis research utilizes a unique approach to assess managerially relevant topics through a "magic wand" interviewing technique (i.e. "If we gave you a magic wand and granted you just one wish, what would you wish for to improve your supply chain?").

Context The Illinois Department of Natural Resources was mandated by legislation to develop management plans for American Black Bears and needed Illinois residents' preferences for bear management strategies. Aims The aim of this article was to examine how demographics, emotions and attitudes were related to support for three American black bear management strategies (active reintroduction, natural recolonisation, having breeding populations of black bears). Researchers have repeatedly suggested that these predictors are related to support for management actions. Methods Data were obtained from a mail survey sent to two populations of stakeholder groups. A total of 896 agricultural producers completed the questionnaire (response rate = 36%); 904 hunters completed the questionnaire (response rate = 36%). Five demographic variables were used in the analyses: (1) agricultural producer; (2) hunter; (3) age; (4) sex; and (5) residence growing up. Positive and negative emotional dispositions were operationalised with eight items. General attitude toward bears was measured with four items. All three management questions were asked for 'in Illinois' and 'in my county'. Reliability analyses supported combining the psychological variables into indices for each construct. Key results Findings indicated that demographic and psychological characteristics are related to support for bear management strategies, but that these relationships are complex for a number of reasons. First, the regression beta coefficients for the demographic regression models were 'minimal' (M = 0.13), whereas the coefficients for psychological variables were 'typical' (M = 0.30). Second, not all of the demographic and psychological variables affected support for agency actions in the same way. Third, the average R2 for the three demographic models was only 16%, whereas the average R2 for the three psychological characteristics models was 53%. Conclusions Given the weak relationships between demographics and support for bear management, managers may not need to always target specific groups based on their demographics. Implications Certain situations may warrant specific messages to target audiences; weak demographic relationships suggest that managers should be cautious when using these characteristics to target communication messages to specific groups.