Staffing Decisions Research Articles

A simulation-based decomposition approach for two-stage staffing optimization in call centers under arrival rate uncertainty

We study a solution approach for a staffing problem in multi-skill call centers. The objective is to find a minimal-cost staffing solution while meeting a target level for the quality of service to customers. We consider a common situation in which the arrival rates are unobserved random variables for which preliminary forecasts are available in a first stage when making the initial staffing decision. In a second stage, more accurate forecasts are obtained and the staffing may have to be modified at a cost, to meet the constraints. This leads to a challenging two-stage stochastic optimization problem in which the quantities involved in the (nonlinear) constraints can only be estimated via simulation, so several independent simulations are required for each first-level scenario. We propose a solution approach that combines sample average approximation with a decomposition method. We provide numerical illustrations to show the practical efficiency of our approach. The proposed method could be adapted to several other staffing problems with uncertain demand, e.g., in retail stores, restaurants, healthcare facilities, and other types of service systems.

Environmental Management by Faith Based Organizations in Uganda: A SWOT Analysis

Faith Based Organizations (FBOs) play a significant role in environmental management in Uganda. Despite this, they have been largely ignored in scholarship leading to a significant gap in understanding activities they carry out and challenges they encounter in environmental management. This study explored the strengths, weaknesses, opportunities and threats associated with environmental management by the FBOs in Uganda. FBOs selected and studied were the Roman Catholic Church, Anglican Church of Uganda, the Muslim Faith, Pentecostal Assemblies of God and the Seventh day Adventist, since they consist over 86% of Uganda’s population. Qualitative and quantitative research strategies with systematic and purposive sampling techniques were used. SWOT analysis using Key Informant Interviews and questionnaires were carried out to obtain information from seven (7) key decision-making staff at the FBOs’ headquarters and 75 from regional centers. Quantitative and qualitative data were analyzed by descriptive statistics and content analysis respectively. Key strengths of FBOs in environmental management include; land ownership, skilled human resources and finances. Existence of good structures from grassroots to national level, knowledge in environmental management and an extensive following countrywide boosts the capacity of FBOs to engage in environmental management activities. Major areas that need improvement are; knowledge and skills in environmental management of leaders and followers; resource mobilisation skills and interest in environmental conservation among most clergy and Imams. Key opportunities were; existence of large number of employees and followers who can be trained in environmental management and the structures from grass-root to national level. Key threats were human population explosion, poverty, land grabbing and unfavourable land tenure and policy changes. FBOs are instrumental in environmental management but are constrained by financial resources, limited knowledge and skills in environmental management and fundraising abilities. This calls for capacity building in these aspects in order to impart the required knowledge and skills to FBOs leaders and followers. Government and other able stakeholders should support FBOs in their endeavor to conduct environmental management activities in Uganda.

Adapting clinical pharmacy staffing models during the COVID‐19 pandemic: Lessons learned and considerations for future disaster planning

AbstractIntroductionIn response to the coronavirus disease 2019 (COVID‐19) pandemic, health care institutions have faced challenges necessitating operational agility to facilitate provision of optimal patient care. This research was performed to elucidate how pharmacy departments adapted their staffing models, and the impact on frontline staff satisfaction.MethodsCritical care pharmacists in the American College of Clinical Pharmacy (ACCP) and the American Society of Health‐System Pharmacists list‐serves were electronically invited to participate in a 28‐question survey between April and May 2020. Likert‐like questions used a 1 to 5 (strongly agree to strongly disagree) scale, and responses were compared based on the degree of satisfaction with implemented pharmacy leadership strategies. Practice model changes were compared before and during the COVID‐19 pandemic. Multivariate logistic regression was used to assess the effects of independent variables on the primary outcome ‐ satisfaction with pharmacy leadership response.ResultsRespondents (N = 168) representing 40 states in the United States participated. Forty percent of respondents experienced a surge, 68% experienced a staffing model change, and 65% were satisfied overall with their pharmacy leadership's response to the COVID‐19 pandemic. Both specialists (50% vs 21%, P = .013) and unit‐based generalists (65% vs 35%, P < .001) rounded less frequently in response to the COVID‐19 pandemic. Disagreement with “Satisfied with leadership efforts to protect staff (limiting in‐person meetings, changing code response)” decreased the odds of satisfaction by 96% (odds ratio [OR] 0.043 [95% confidence interval (CI) 0.005‐0.336], P = .003). Disagreement with “Satisfied with voice of front‐line staff” was associated with an 84% reduction in satisfaction (OR 0.165 [95% CI 0.049‐0.549], P = .003). Eliminating in‐person rounds was associated with a 95% decrease in satisfaction with pharmacy leadership (OR 0.053 [95% CI 0.007‐0.392], P = .004). Disagreement with “I believe I am at increased risk for COVID‐19 due to departmental staffing decisions” increased satisfaction (OR 3.8, 95% CI [1.06‐13.91], P = .041).ConclusionFrontline staff perceptions can inform practice model changes to improve employee satisfaction while providing safe, reliable, and responsible patient care.

Validating Human Performance Models: Building a House without Bricks

Verification and validation (V&V) for human performance models (HPMs) can be likened to building a house with no bricks, since it is difficult to obtain metrics to validate a model when the system is still in development. HPMs are effective for performing trade-offs between the human system designs factors including number of operators needed, the role of automated tasks versus operator tasks, and member task responsibilities required to operate a system. On a recent government contract, our team used a human performance model to provide additional analysis beyond traditional trade studies. Our team verified the contractually mandated staff size for using the system. This task demanded that the model have sufficient fidelity to provide information for high confidence staffing decisions. It required a method for verifying and validating the model and its results to ensure that it accurately reflected the real world. The situation caused a dilemma because there was no actual system to gather real data to use to validate the model. It is a challenge to validate human performance models, since they support design decisions prior to system. For example, crew models are typically inform the design, staffing needs, and the requirements for each operator’s user interface prior to development. This paper discusses a successful case study for how our team met the V&V challenges with the US Air Force model accreditation authority and successfully accredited our human performance model with enough fidelity for requirements testing on an Air Force Command and Control program.

Is distributed leadership an effective approach for mobilising professional capital across professional learning networks? Exploring a case from England

PurposeThere is currently a focus on using networks to drive school and school system improvement. To achieve such benefits, however, requires school leaders actively support the mobilisation of networked-driven innovations. One promising yet under-researched approach to mobilisation is enabling distributed leadership to flourish. To provide further insight in this area, this paper explores how the leaders involved in one professional learning network (the Hampshire Research Learning Network) employed a distributed approach to mobilise networked learning activity in order to build professional capital.Design/methodology/approachA mixed methods approach was used to develop a case study of the Hampshire RLN . Fieldwork commenced with in-depth semi-structured interviews with all school leaders of schools participating in the network and other key participating teachers (12 interviews in total). A bespoke social network survey was then administered to schools (41 responses). The purpose of the survey was to explore types of RLN-related interaction undertaken by teachers and how teachers were using the innovations emerging from the RLN within their practice.FindingsData indicate that models of distributed leadership that actively involves staff in decisions about what innovations to adopt and how to adopt them are more successful in ensuring teachers across networks: (1) engage with innovations; (2) explore how new practices can be used to improve teaching and learning and (3) continue to use/refine practices in an ongoing way.Originality/valueCorrespondingly we argue these findings point to a promising approach to system improvement and add valuable insight to a relatively understudied area.

Optimal Staffing for Online-to-Offline On-Demand Delivery Systems: In-House or Crowd-Sourcing Drivers?

Online-to-offline (O2O) on-demand services require one-hour delivery and the demands vary substantially within one day. The capacity plans in the O2O industry evolve into three main modes: (i) in-house drivers only; (ii) full-time and part-time crowd-sourcing drivers; (iii) a mix of in-house and crowd-sourcing drivers. For current capacity plans, two issues remain unclear for both academia and industry. First, what is the optimal staffing decision when considering the behaviors of crowd-sourcing drivers. Second, how to choose from different capacity plans to match different operation strategies and market environments. To address these questions, we build an M/M/n queueing model to optimize the staffing decision with the aim of minimizing the total operation costs. Incentive mechanisms for both customers and crowd-sourcing drivers are crafted to improve their loyalty towards the O2O platform, in order to better manage capacity. Moreover, we apply a real dataset from one of the largest O2O platforms in China to verify our model. Our analyses show that adding flexibility — capacity-type flexibility and agent flexibility — to the O2O on-demand logistics system can help control costs and maintain a high service level. Furthermore, conditions in which different capacity plans match with different operation strategies and market environments are proposed.

Staff-Related Disclosures as an Element of Social Policies on the Model of Bulgarian Black Sea Hotels

The main aim of the study is to analyse published information on staff-related social policies on the websites and in the annual financial statements of enterprises that manage hotels and provide hotel services in the territory of Varna and Burgas Black Sea regions in Bulgaria. In addition, analysed are some factors that impact disclosures in the financial statements of enterprises. The adopted research methods are the logical, deductive and comparative methods, as well as the methods of analysis and synthesis. To verify the author's hypotheses the IBM – SPSS Statistics software, ver. 19 has been used. The main results of the study show that the analysed hotel enterprises disclose scarce or no information on staff related data and social policies on their websites or in their financial statements. Disclosures mainly focus on compliance with legal requirements and they are most significantly influenced by available audit control and selected accounting basis. This could lead to asymmetry in the data, lowering the prestige of the organisation, problems with recruitment of qualified staff and unjustified economic decisions by data users

Decision making under uncertain and dependent system rates in service systems

In this paper, we propose decision analysis methods for determining the optimal number of agents of a service system where the system rates (arrival, service, and abandonment) are modeled as dependent random variables. In doing so, we take the Bayesian point of view of inference and obtain joint posterior distributions of the system rates. We solve the proposed stochastic staffing decision problem with augmented probability simulation based optimization methods. The novelty of our approach stems from the use of dependent system rates to determine optimal staffing in a constrained optimization setting for stochastic service systems. We demonstrate the implications of ignoring dependence and uncertainty in system rates on simulated data for general service systems, and illustrate the application of the proposed methodology on call center operations.

A mathematical programming model for facility location optimization of hydrogen production from renewable energy sources

ABSTRACT Fossil fuels are the primary energy sources and meet the global energy demands. However, environmental and health problems related with these sources boosted the demand for renewable energy sources. Hydrogen, as an energy carrier has a growing potential for solving these problems. In this article, a mathematical programming model that integrates the production, storage and transportation, safety, location, and staff assignment decisions is presented considering minimization of costs. Although most of the studies focus on location, distribution, storage decisions of hydrogen energy networks, the article also includes production, safety and staff assignment decisions to make this problem more practical. Furthermore, we also investigate the set covering constraint will ensure that each region is covered by minimum number of the hydrogen facilities. The developed model ensures a balance between location, distribution, storage, production, safety and staff decisions by installing two production facilities by assigning total 9 warehouses, 22 tank trucks, 12100 km pipeline, 35 staffs under distance constraint 2000 km in regions 1 and 5. The computational results indicate that the proposed model produces effective solutions for the coverage to all region and minimum total cost for real-case situations.

Industrial exhibitors' resource commitment to booth personnel: A study of select predictors and consequences

Within the context of industrial exhibitions, few researchers have explored how booth staffing decisions affect the booth personnel's reactions and conduct at trade shows. In the current study, Narver and Slater's market orientation dimensions are considered as the predictors of exhibitor's booth personnel commitment. Besides, this study explores the impacts of exhibitor's booth personnel commitment on booth worker's role clarity, goal acceptance, and work effort. Finally, the influences of work effort on three forms of booth staff's information behavior are tested. The data collected from five different B2B exhibits in Taiwan support eleven of the twelve hypotheses. Based on the analytic results, the present research adds theoretical and managerial implications to the existing literature of industrial exhibitions. In particular, it highlights three issues for exhibitors to consider, which include process ambiguity, interaction adaptation, and informational paradox.

Patient monitoring as a predictor of blood culture results in a tertiary neonatal intensive care unit

We present a mesoergonomic approach to the early detection of neonatal sepsis, analyzing clinical data for 4999 patients from a neo-natal intensive care unit to predict positive culture results. The Apgar score at birth predicted positive results. For neonates with poor and intermediate Apgar scores, culture results for monitored infants were more likely to be positive than those for unmonitored infants. Thus, the medical staff tended to monitor infants who eventually had a greater chance for positive test results. A cost-effectiveness analysis indicated that for infants with high Apgar scores, the physician should decide whether to obtain a blood culture, based on the patient's characteristics. For infants with lower Apgar scores, it may be advisable to obtain a blood culture whenever one decides to monitor a neonate. The study demonstrates that staff decisions regarding a patient can serve as input for further clinical decision-making.

Early warning systems in biosecurity; translating risk into action in predictive systems for invasive alien species.

Invasive alien species (IAS) are one of the most severe threats to biodiversity and are the subject of varying degrees of surveillance activity. Predictive early warning systems (EWS), incorporating automated surveillance of relevant dataflows, warning generation and dissemination to decision makers are a key target for developing effective management around IAS, alongside more conventional early detection and horizon scanning technologies. Sophisticated modelling frameworks including the definition of the 'risky' species pool, and pathway analysis at the macro and micro-scale are increasingly available to support decision making and to help prioritise risks from different regions and/or taxa. The main challenges in constructing such frameworks, to be applied to border inspections, are (i) the lack of standardisation and integration of the associated complex digital data environments and (ii) effective integration into the decision making process, ensuring that risk information is disseminated in an actionable way to frontline surveillance staff and other decision makers. To truly achieve early warning in biosecurity requires close collaboration between developers and end-users to ensure that generated warnings are duly considered by decision makers, reflect best practice, scientific understanding and the working environment facing frontline actors. Progress towards this goal will rely on openness and mutual understanding of the role of EWS in IAS risk management, as much as on developments in the underlying technologies for surveillance and modelling procedures.

Safety and Feasibility of Outpatient High Dose Cytarabine for Acute Myeloid Leukemia in the Brazilian Amazon.

Background: The attempt to manage patients with acute myeloid leukemia as outpatients has become increasingly common due to high hospitalization costs, low availability for beds and patient preference. Publications on the subject are scarce, especially in low-income regions and the safety in this population remains to be determined. The present study aims to assess the safety of consolidation with high-dose cytarabine in the outpatient setting. Materials and Methods: We retrospectively analyzed 39 patients who underwent consolidation with high-dose cytarabine, between 2009 and 2018, at Ophir Loyola Hospital, in Belém, Brazil. Patients treated after 2015 were given high-dose cytarabine as outpatients due to the decision of medical staff. Results: Twenty-seven patients received 76 cycles of cytarabine as outpatients; males were 48.14% of the total population, with a median age of approximately 45 years. The occurrence of delay between cycles was significantly lower among outpatients (48.14% vs. 83.33%, p = 0.04). There was no difference in relapse rates, transfusion requirements and non-relapse mortality between both groups. Hospitalization was required in 40.74% of patients during outpatient cycles and 18.51% of blood cultures were positive for pathogens. Non-relapse mortality was significantly higher among patients above 50 years old and treated on an outpatient basis (44.4% vs. 5.60%, p = 0.03). Conclusion: High-dose cytarabine administration on an outpatient basis appears to be safe and effective in a low-income population at the Brazilian Amazon region, but toxicity seems to be increased for patients older than 50 years.

Attracting, recruiting and retaining nurses and care workers working in care homes: the need for a nuanced understanding informed by evidence and theory.

The care home sector relies on nurses and care workers to deliver care to residents living with frailty and complex needs. However, attracting, recruiting and retaining staff is one of the biggest challenges facing this sector. There is evidence available that describes factors that influence staff decisions to join and/or remain in the care home workforce, for example, individual rewards (such as feeling valued at work or training opportunities), relationships with colleagues and residents, supportive management or working arrangements (including flexible hours). However, it is less clear how different strategies are informed by evidence to improve recruitment and retention. Care homes are heterogeneous in terms of their size, staffing levels and mix, staff age groups, geographical location and working conditions. What matters to different members of the care home workforce will vary across nurses and care workers of different ages and levels of qualification or experience. Recognising this diversity is key: understanding how to attract, recruit and retain staff needs to discriminate and offer solutions that address this diversity. This important area of practice does not lend itself to a 'one-approach-fits-all' solution. This commentary provides a brief overview of known workforce challenges for the care home sector and argues for studies that use empirical evidence to test different theories of what might work for different staff, how and why, and in different circumstances.

The effectiveness of university regulations to foster science-based entrepreneurship

In this study, we analyze the effect of the introduction of university regulations supporting academic entrepreneurship. Using a sample of 611 companies spun-off from the 64 Italian Science, Technology, Engineering, Mathematics and Medicine (STEMM) universities between 2002 and 2012, we show that university regulations in support of academic entrepreneurship have a positive effect on the creation of academic spin-offs. Nevertheless, their effectiveness is conditioned by specific contingencies. First, the characteristics of university departments influence the positive effect of the regulation: in some cases, there is a substitution effect rather than a complementary one. Second, the design of the regulation impacts the decisions of academic staff regarding whether to start a new venture. Finally, the effect of the regulation is maximized four years after its introduction and then becomes less effective. This paper contributes to the debate on the evaluation of policies supporting science-based entrepreneurship.

Analysis of Question Type Can Help Inform Chat Staffing Decisions

A Review of:
 Meert-Williston, D., & Sandieson, R. (2019). Online Chat Reference: Question Type and the Implication for Staffing in a Large Academic Library. The Reference Librarian, 60(1), 51-61. http://www.tandfonline.com/doi/full/10.1080/02763877.2018.1515688
 Abstract
 Objective – Determine the type of online chat questions to help inform staffing decisions for chat reference service considering their library’s service mandate.
 Design – Content analysis of consortial online chat questions.
 Setting – Large academic library in Canada.
 Subjects – Analysis included 2,734 chat question transcripts.
 Methods – The authors analyzed chat question transcripts from patrons at the institution for the period of time from September 2013 to August 2014. The authors coded transcripts by question type using a coding tool created by the authors. For transcripts that fit more than one question type, the authors chose the most prominent type.
 Main Results – The authors coded the chat questions as follows: service (51%), reference (25%), citation (9%), technology (7%), and miscellaneous (8%). The majority of service questions were informational, followed by account related questions. Most of the reference chat questions were ready reference with only 16% (4% of the total number of chat questions) being in-depth. After removing miscellaneous questions, those that required a high level of expertise (in-depth reference, instructional, copyright, or citation) equaled 19%.
 Conclusion – At this institution, one in five chat questions needed a high level of expertise. Library assistants with sufficient expertise could effectively answer circulation and general reference questions. With training they could triage complex questions.

Prescriptive Call Center Staffing

This paper addresses the call center staffing problem. We present a novel prescriptive staffing approach that minimizes the human labor cost and the cost for calls that were abandoned due to excessive waiting times. Our approach is novel in that it determines a prescriptive model based on the functional relationship between observable features such as call volumes in previous staffing segments, school holidays or other events and the optimal staffing decision. In order to abstain from strong assumptions about underlying data distributions, we learn the model from historical data by combining the staffing cost optimization problem with a machine learning algorithm. We analyze the performance of our approach on two real-world data sets and compare it to a state-of-the-art benchmark. Provided with the same information as the benchmark, our approach dominates on both data sets, resulting in a cost improvement of up to 8 percentage points and shows even greater cost improvements when provided with additional features. We can explain the cost advantage of our approach in part with its ability to consider non-random intra-slot patterns in the call arrival such as a trend.

Permission to Narrate a Pandemic in Palestine

Permission to Narrate a Pandemic in Palestine

Retail in High Definition: Monitoring Customer Assistance Through Video Analytics

Problem definition : We consider the development of an efficient and scalable video-analytics approach to measure customer assistance and its mediating role in the relationship between staffing levels and revenues. Academic/practical relevance : Staffing decisions account for a large portion of a retailer’s operational costs. Researchers have studied the extent to which an increase in staffing levels translates into greater revenues, without emphasizing the underlying mechanisms that generate this potential improvement, such as assisting customers. Methodology : We use econometric methods, including survival-analysis techniques, to analyze data gathered from in-store video recordings of customer visits to stores of a women’s apparel chain. Results : We find that, under average store conditions, a 25% increase in labor yields a 16% increase in store revenues. An increase in the assistance of customers while searching, browsing, or trying products mediates approximately 50% of this increase, while the remainder originates from other activities, such as helping customers at the checkout counter. Moreover, we find that this form of assistance has a significant and positive impact on both conversion and ticket size. Managerial implications : Our approach can be used to explain heterogeneity in employee productivity across stores, to monitor and detect unexpected deviations in customer-assistance levels, and to measure the productivity of multitasking agents for the different functions that they perform.

School Climate: A Comparative Study from the Perspective of Kindergarten Principals and Teachers

The aim of this study is to determine the school climate in formal kindergartens, to examine the factors affecting it and its effect on education and to use teachers and school principals’ views to point out the elements necessary for its improvement. Partially mixed sequential dominant status design, which is a two-stage (qualitative and qualitative) mixed design was used in the study. In the first stage, 115 teachers and 34 school principals of 18 independent kindergartens in Eskisehir were administered an Organizational Climate Scale to determine the working climates of the kindergartens. In the second stage, semi-structured interviews were conducted with the teachers and principals of the two schools with the highest and lowest scale scores to investigate the reasons for the differences in school climates and their effect on education. Principals’ personalities and their communication and problem solving skills, and support, praise and encouragement given to teachers, fair behavior, openness to new ideas and involving staff in decision making play an important role in creating a positive school climate. School climate has a great impact on students through teachers and staff.