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This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides decision makers an assessment of a proposed station location’s ability to support a unit’s personnel requirements from the local population.

This research first develops an allocation method to overcome challenges caused by overlapping unit boundaries to prevent over-counting the population. Once populations are accurately allocated to each location, we then then develop and compare the performance of statistical models to estimate a location’s likelihood of meeting staffing requirements.

This research finds that local demographic factors prove essential to a location’s ability to meet staffing requirements. We recommend that the USAR and US Army Recruiting Command (USAREC) use the logistic regression model developed here to support USAR unit stationing decisions; this should improve the ability of units to achieve required staffing levels.

This research meets a direct request from the USAREC, in conjunction with the USAR, for assistance in developing models to aid decision makers during the unit stationing process.

THE extraordinary general meeting of January 6 1982 called upon the LA Council to commission an independent management audit into the association's finances. This was to go much further than a mere accounting check. Since the LA already employs a firm of auditors, the same firm for sixty years, at a cost of £4590 in the year ended December 31 1980, many might have questioned the need for an additional audit.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/eb014418. When citing the article, please cite: Robert G. House, Jeffrey J. Karrenbauer, (1978), “Logistics System Modelling”, International Journal of Physical Distribution & Materials Management, Vol. 8 Iss: 4, pp. 189 - 199.

This study examines the institutional setting and decision-making structures among key industry actors in the Malaysian housing industry, using the IMP network approach and institutional theory as theoretical lenses. The purpose of this study is to uncover the role of NGOs, housing developers and the government at a collective level within a highly regulated housing market. This study uses “relationships” as the unit of analysis, focusing on triadic interactions of NGOs, housing developers and the government.

This study applies the qualitative case-study-research approach, using 20 in-depth interviews from the purposefully selected industry actors within the housing market, online observations and documents.

The findings suggest that NGOs play an influential role in housing-industry interactions and outcomes. In particular, the Real Estate and Housing Developers Association can influence the members’ decisions through supportive and disruptive actions.

This study contributes to our understanding of how NGOs interact with their regulator and housing developers and how these three parties co-evolve and respond to institutional demands in a housing market that is bound by a highly restricted housing policy. By understanding how actors interact within a network and how it affects each other’s decision, it may assist policymakers in formulating policies that can improve market efficiency. It also aids businesses in formulating their collective strategies.

In a logistics system the number of possible applications of qualitative and quantitative modelling efforts is practically infinite. The situations or problems which can be analysed range from micro operations (e.g., analysing alternative order picking systems) to macro planning issues (e.g., determining the number and location of warehouses to be employed in a future distribution system). This range of potential applications not only reflects the scope of the models (micro to macro) but it also incorporates another relevant dimension: planning. The planning axis is anchored at one end by operations models which are constructed to analyse daily operating practices. The other end of the continuum is represented by long range planning models. These models are used to aid logistics managers in their attempts to design systems to cope with the future. In many situations exact classification of individual models along these two dimensions is difficult. However, this categorisation is a useful framework within which to view the scope of the modelling discussed in this paper. This presentation will focus on the macro planning models that are being employed both in military and industrial logistics to aid the systems planner in his attempts to structure logistics systems for the future.

Entrepreneurship.

This case is suitable for graduate-level programmes in business management, as well as for executive education programmes.

Mabel Simpson, the sole proprietor of the award-winning mSimps fashion accessories house in Ghana, must choose from among three options for scaling up her business: an offer from a private investor for GHS 100,000 in exchange for 51 per cent stake in mSimps; or 30 per cent stake for half the amount; an offer from a fashion industry expert for GHS 10,000 in exchange for 30 per cent ownership; or a restructuring of her business model and value chain to enable her release cash to grow her business organically.

Students should be able to: understand the interplay of choice and trade-offs in business management and apply theory-driven frameworks in making optimal choices and analytically assess instances of tension between the art (e.g. passion, emotional stakes, psychological and other influences on business management philosophies) and science (e.g. the need for business skills, use of effective models and the quest for production efficiency) of business management.

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CSS 3: Entrepreneurship

The purpose of this study is to explain the potential long-term impacts of working from home on housing wealth inequality in large cities of advanced economies.

This study is descriptive research and It supports the arguments by providing some emerging evidence from property markets in developed countries.

The authors argue that due to the unique nature of the COVID-19 crisis, it will have a different and long-term impact on housing wealth inequality. Changes in the working arrangements of many professionals will change the housing demand dynamic across different suburbs and may lead to a reduction of the housing wealth gap in the long term. In this paper, the authors propose five mechanisms that may impact housing wealth inequality.

Long-term data is required to test the proposed conceptual model in this study and the effect of the COVID-19 pandemic on housing wealth across and within suburbs of large cities.

Policymakers and regulators may benefit from the discussions and suggestions provided in this study and consider the proposed avenues on how new changes in the working environment (remote working) may result in a reduction of housing wealth inequality.

This study presents a new perspective about the potential long-term impacts of working from home that is posed by the COVID-19 pandemic on housing wealth inequality in large cities of developed economies.

Housing prices in the UK offer an inspiring, yet a complex and under-explored research area. The purpose of this paper is to investigate the critical factors that affect UK’s housing prices.

The authors utilize the recently developed nonlinear ARDL approach of Shin et al. (2014) over the period 1969–2016.

The authors find that both the long-run and short-run impact of the price-to-rent (PTR) ratio and credit-to-GDP ratio on house prices (HP) is asymmetric whilst ambiguous results are established for mortgage rates, industrial production and equities. Apart from the novel framework of analysis, this study also establishes a positive association between HP and the PTR ratio which suggests a speculative behaviour and could imply the formation of a housing bubble.

It is the first study for the UK housing market that explores the underlying fundamental relationships by looking at nonlinearities hence, allowing HP to be tied by asymmetric relationships in the long as well as in the short run. Modelling the inherent nonlinearities enhances significantly the understanding of UK housing market which can prove useful for policymaking and forecasting purposes.

The purpose of this paper is to analyze the relationship between housing markets and new firm formation in six different industries in all 284 municipalities in Sweden.

The authors have used data from Statistics Sweden and The Swedish Agency for Economic and Regional Growth to develop a model to analyze the relationship between house prices and industry-specific new firm formation, with the interaction effect of financial infrastructure.

In the data, stable high house prices have no effect on entrepreneurship. However, a market with rising house prices has a positive effect on new firm formation, in retail, construction, business-to-business services and miscellaneous sectors, but produced no effect in either mining, agriculture and fishing or in manufacturing. The interaction between rising house prices and financial infrastructure does not change the positive effect on retail, business-to-business services and miscellaneous sectors, but within the construction industry, the positive effect on new firm formation disappears. In manufacturing, the authors observe the opposite – a positive effect, instead of no effect previously.

The contribution of this study is to provide evidence of how house prices are associated with entrepreneurship in different industries, as well as analyzing how the interaction between house prices and financial infrastructure is associated with entrepreneurship. By separating observations in time, endogeneity is controlled and a causal relationship where higher house prices is postulated, which leads to an increase in entrepreneurial activity in different industries. By using a spatial Durbin model, the authors control for spatial dependency.