Part A- Review of Four Articles

Golicic, S. & Mentzer, J. (2005) Exploring the drivers of interorganizational relationship magnitude, Journal of Business Logistics, Vol 26(2) pp.47-71

The study authored by Golicic & Mentzer, 2005, aims to investigate what factors contribute to various levels of relationship magnitude and attempts to explore contextual drivers influencing relationship magnitude. Golicic, Foggin and Mentzer cited in Golicic & Mentzer (2005) define relationship magnitude as; “the degree or extent of closeness or strength of the relationship amongst organisations” (p. 47).

Areas in the literature that have been critiqued include historical views on the structure of relationships broken down into two main components; the economic structure (‘type’) and policy in terms of strength and closeness of relationships (‘magnitude’). Additionally the authors critique the business press who have advocated the need for firms to build and maintain closer, long term relationships with suppliers and customers. A number of different studies are cited supporting the notion that some firms don’t want or need these closer relationships.

The methodology used to collect data for the research was a qualitative method of content analysis of depth interviews.

The results from the content analysis of depth interviews identified eight contextual drivers which the authors note as; capabilities, expected benefits, external influence, history, importance, interpersonal interaction, performance and strategy congruence. The authors discuss the drivers in detail and underpin their findings with further literature support but make the distinction that only in specific cases do the drivers relate to magnitude of a relationship over type.

An opportunity for further research identified by the authors is in developing further hypotheses for the contextual drivers that have been presented and testing these for validity in a manner that is perhaps more robust than the qualitative analysis presented.

Jackson, S. Wilson, J. McCarthy, B. (2004) A new model of scheduling in manufacturing: tasks, roles and monitoring, Human Factors, Vol 46(3)

The paper authored by Jackson et al. 2004, aims to present a new production scheduling model representative of the significant facilitation and implementation aspects of human scheduling that is ignored by many computational generated scheduling models.

Areas in the literature that have been critiqued include research that has previously attempted to develop models of human scheduling in manufacturing contexts and research that has explored the scheduler activities of task, roles and monitoring.

The authors present a descriptive model of scheduling performance that captures scheduler behaviour and performance considered more appropriate than previous theoretical scheduling models.

The methodology used for collecting data to present the new scheduling model was a qualitative field study comprising of two techniques; direct observation and retrospective decision probes.

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The results indicated that schedulers presented three distinct types of activities in their jobs, namely; tasks, roles, and monitoring. Another key finding was that schedulers do not carry out all tasks in a sequential manner all of the time and that scheduling roles change over time because of external factors that influence the scheduling function, such as uncertainty and inherent instability of the business environment.

An area identified for further research was to establish how the new model of scheduling may be utilised in the context of both existing and new production planning & control and enterprise information systems.

Ritschel, D. Greiner, M. Reynolds, D. Seibel, M. (2003) Flyaway costs versus individual components of aircraft: An analysis, Air Force Journal of Logistics, Vol 27(4) 30 pp.32-47

The article authored by Ritschel et al. aims to investigate and measure the risks associated with taking a macro versus micro approach to aircraft cost estimation. The fidelity of a cost estimate developed at the flyaway cost level (macro) versus at the individual component level (micro) is analysed in order to provide program manager’s with guidelines for appropriate allocation of cost analysts in today’s constrained environment.