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Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces errors. Significant theoretical research has been performed related to the modifiable areal unit problem and the zone definition problem. Minimal research has been accomplished related to the specific issues inherent to spatiotemporal demand data, such as search and rescue (SAR) data. This study provides a quantitative comparison of various aggregation methodologies and their relation to distance and volume based aggregation errors.

This paper introduces and applies a framework for comparing both deterministic and stochastic aggregation methods using distance- and volume-based aggregation error metrics. This paper additionally applies weighted versions of these metrics to account for the reality that demand events are nonhomogeneous. These metrics are applied to a large, highly variable, spatiotemporal demand data set of SAR events in the Pacific Ocean. Comparisons using these metrics are conducted between six quadrat aggregations of varying scales and two zonal distribution models using hierarchical clustering.

As quadrat fidelity increases the distance-based aggregation error decreases, while the two deliberate zonal approaches further reduce this error while using fewer zones. However, the higher fidelity aggregations detrimentally affect volume error. Additionally, by splitting the SAR data set into training and test sets this paper shows the stochastic zonal distribution aggregation method is effective at simulating actual future demands.

This study indicates no singular best aggregation method exists, by quantifying trade-offs in aggregation-induced errors practitioners can utilize the method that minimizes errors most relevant to their study. Study also quantifies the ability of a stochastic zonal distribution method to effectively simulate future demand data.

This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and vertex-greedy subclasses. As these subclasses of heuristics can create subtours, two known methodologies for subtour elimination on symmetric instances are reviewed and are expanded to cover asymmetric problem instances. This paper introduces a third novel subtour elimination methodology, the greedy tracker (GT), and compares it to both known methodologies.

Computational results for all three subtour elimination methodologies are generated across 17 symmetric instances ranging in size from 29 vertices to 5,934 vertices, as well as 9 asymmetric instances ranging in size from 17 to 443 vertices.

The results demonstrate the GT is the fastest method for preventing subtours for instances below 400 vertices. Additionally, a distinction between fragment constructive heuristics and the subtour elimination methodology used to ensure the feasibility of resulting solutions enables the introduction of a new vertex-greedy fragment heuristic called ordered greedy.

This research has two main contributions: first, it introduces a novel subtour elimination methodology. Second, the research introduces the concept of ordered lists which remaps the TSP into a new space with promising initial computational results.

This study aims to identify how the personal social capital of opinion leaders contributes to the market adoption of start-up innovations.

A design-oriented case study is undertaken with a start-up company focusing on the development and commercialization of innovations in the veterinary market. Based on a literature review, the authors examine the social capital in value creation and the role of opinion leaders and use qualitative methodology and semi-structured in-depth interviews to collect data.

The adoption of innovations could start with opinion leaders that will later share their experience with other members of the professional community. In turn, social capital allows for creating a collaboration between start-ups and leaders based on a number of specific parameters.

This paper contributes to marketing literature by providing new insights regarding collaboration between start-ups and opinion leaders. The collaboration between opinion leaders and start-ups could be implemented not only in the veterinary industry but also in other industries with minor adaptations. Authors demonstrate how the social capital of external stakeholders may be used as a resource of the company for business development. The main contribution of this study is to demonstrate that social capital could be used as a parameter for the adoption of innovations. The key parameters that allow creating cooperation between start-up and opinion leader have been identified.

An understanding of the motivation of individual employees to adopt lean practices is fundamental to successful lean implementation. This study aims to investigate the adoption of lean practices and provides an analysis of the individual-level factors necessary for lean implementation. This study presents a method for assessing the impact of individual-level factors in a company deploying lean within a biopharmaceutical manufacturing subsidiary.

The case study explores the attitudes of individuals within a functionally structured organisation undergoing a lean implementation initiative. A quantitative data collection approach was used to capture data from employees in a medical device manufacturing organisation.

The study found that personality and affective organisational commitment positively affects an individual’s intention to adopt lean practices. Employees with greater levels of affective commitment are more likely to partake in lean-related practices. Individuals in functions that directly support the production process, as opposed to those in functions that indirectly support production, are more likely to participate in lean practices. Finally, individuals in supervisory roles are more likely to adopt lean practices than those in non-supervisory roles, and management should involve top performers in lean.

There is a paucity of case study research in the area of individual-level factors for lean practice adoption. The findings of this study offer practical guidance on individual-level factors for lean practice adoption and illuminate new avenues for future research. This analysis also makes a practical contribution to the literature. From a managerial perspective, understanding why certain employees are more willing to adopt lean practices contributes to an overall lean organisational readiness and implementation framework. This insight enables the development of carefully tailored communication and training programs for managing employee motivation for and receptivity to lean.