Editorial

Citation

Burgess, T.F. and Heap, J. (2015), "Editorial", International Journal of Productivity and Performance Management, Vol. 64 No. 8. https://doi.org/10.1108/IJPPM-09-2015-0121

Editorial

Article Type: Editorial From: International Journal of Productivity and Performance Management, Volume 64, Issue 8.

This last issue of the 64th volume consists of five standard papers. As usual the journal contains papers that cover a mix of topics and contexts. Authors come from across the globe with contributions from Australia, India, Turkey, and the UK. Papers span contexts and topics that vary from public sector to private sector, manufacturing to service, individual organisations to supply chains, operations to marketing, automotive production to agriculture, office work to shop floor, and so on.

With today's increasing emphasis on knowledge, rather than physical, work the scope of productivity improvement is evolving along with changes in the required methods and techniques to achieve such improvement. The first paper illustrates this changing landscape of productivity work by looking at how to improve the accuracy of engineering documents and thereby improve the productivity of engineers who have to work with such documents. The authors (Zhou, Love, Matthews, Carey, Sing and Edwards) describe, by way of a case study, how a new approach to recording documents can improve the productivity of engineers by such as reducing errors and duplication. This interesting paper also sparks the thought that there could be more of this type of study where productivity improvement intersects with knowledge work. The journal's editors would be interested in seeing more papers of this type.

Although it has long been held that marketing is a key capability that affects firm performance; the authors of the next paper contend that the knowledge of how marketing capability (MC) influences firm performance (FP) is still fragmented and poorly understood. In the second paper Kamboj and Rahman present their literature review that more firmly establishes the knowledge base for this important relationship. This systematic, focussed review establishes a valuable resource for future research linking MC and FP. The inclusion in the review of only peer-reviewed papers of empirical studies means that their conclusions are relevant to both researchers and practitioners.

In the third paper Piotrowicz and Cuthbertson present the results of an exploratory survey of approaches, tools and metrics used to measure performance in supply chains. Respondents from 51 companies, mainly located in Europe, provide data that are subjected to descriptive analysis. Some of the main approaches used in practice are what one might expect, e.g. balanced scorecard, supply chain operations reference model and economic value added; but a good deal of variety is evident. This suggests there might be some room for standardisation to assist in the development of supply chain performance measurement. The authors also note that economic measures are more prominent than the other two groups of measures (environmental and social) that comprise the triple bottom line of sustainability.

Lean and, in particular, lean in the automotive industry continues to be an important target of much research interest. Much lean research has focused on the top tier of the automotive supply chain with less research on lower tiers. In the issue's fourth paper Garza-Reyes, Ates and Kumar use a survey questionnaire based on an existing framework to evaluate the level of readiness to adopt or sustain lean for 48 Turkish suppliers of automotive parts. Although previous research has explored lean within the companies carrying out main assembly of automobiles in Turkey; exploration of parts suppliers in the country has so far been limited. Overall the study shows satisfactory levels of lean readiness for the parts suppliers but does point to areas that need improving.

The performances of forecasting systems are of major global importance when applied to forecasting matters such as food production and consumption. In the next paper the authors examine how two well-regarded forecasting systems (Bayes and fuzzy inference) perform in forecasting rice production and consumption in India. They examine the extent to which potentially key variables contribute to the accuracy of forecasting models for rice production and consumption over a fifty year period. Their findings will help guide researchers and practitioners in future when deciding how to design systems to forecast food production and consumption.

Thomas F. Burgess and John Heap