Glen D. Murphy

High performance work practices

Significant progress has been made linking innovative human resource (HR) practices such as systems of high performance work practices (HPWPs) to organisational performance. However, evidence would suggest that the rate of adoption of these and other types of HRM innovations is minimal. It was determined that an area not commonly addressed in the literature is the role of the HR practitioner in the adoption process. An argument is presented concerning the pivotal role of the HR practitioner in the adoption process due to their ability to influence a number of contextual dimensions. Research was undertaken to establish the link between the innovativeness of a practitioner and their perceptions regarding the relative importance of individual and contextual factors in the adoption process. Four dimensions, organisational leadership, HR group role, HR group climate and networking skills were identified as being the possible differentiating factors in the successful adoption of HPWPs.

Using social media to facilitate knowledge transfer in complex engineering environments: a primer for educators

While highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Consequently, an essential challenge for engineering organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper acts as a primer for those seeking to gain an understanding of the design, functionality and utility of a suite of software tools generically termed social media technologies in the context of optimising the management of tacit engineering knowledge. Underpinned by knowledge management theory and using detailed case examples, this paper explores how social media technologies achieve such goals, allowing for the transfer of knowledge by tapping into the tacit and explicit knowledge of disparate groups in complex engineering environments.

Improving the quality of manually acquired data: Applying the theory of planned behaviour to data quality

The continued reliance of manual data capture in engineering asset intensive organisations highlights the critical role played by those responsible for recording raw data. The potential for data quality variance across individual operators also exposes the need to better manage this particular group. This paper evaluates the relative importance of the human factors associated with data quality. Using the theory of planned behaviour this paper considers the impact of attitudes, perceptions and behavioural intentions on the data collection process in an engineering asset context. Two additional variables are included, those of time pressure and operator feedback. Time pressure is argued to act as a moderator between intention and data collection behaviour, while perceived behavioural control will moderate the relationship between feedback and data collection behaviour. Overall the paper argues that the presence of best practice procedures or threats of disciplinary sanction are insufficient controls to determine data quality. Instead those concerned with improving the data collection performance of operators should consider the operator’s perceptions of group attitude towards data quality, the level of feedback provided to data collectors and the impact of time-pressures on procedure compliance. A range of practical recommendations are provided to those wishing to improve the quality of their manually acquired data.

Testing a tri-partite contingent model of engineering cultures: A pilot study

For some time there has been a growing awareness of organizational culture and its impact on the functioning of engineering and maintenance departments. Those wishing to implement contemporary maintenance regimes (e.g. condition based maintenance) are often encouraged to develop “appropriate cultures” to support a new method’s introduction. Unfortunately these same publications often fail to specifically articulate the cultural values required to support those efforts. In the broader literature, only a limited number of case examples document the cultural values held by engineering asset intensive firms and how they contribute to their success (or failure). Consequently a gap exists in our knowledge of what engineering cultures currently might look like, or what might constitute a best practice engineering asset culture. The findings of a pilot study investigating the perceived ideal characteristics of engineering asset cultures are reported. Engineering managers, consultants and academics (n=47), were surveyed as to what they saw were essential attributes of both engineering cultures and engineering asset personnel. Valued cultural elements included those orientated around continuous improvement, safety and quality. Valued individual attributes included openness to change, interpersonal skills and conscientiousness. The paper concludes with a discussion regarding the development of a best practice cultural framework for practitioners and engineering managers.

Unpacking ‘lessons learned’: investigating failures and considering alternative solutions

One of the most common ways to share project knowledge is to capture the positive and negative aspects of projects in the form of lessons learned (LL). If effectively used, this process can assist project managers in reusing project knowledge and preventing future projects from repeating mistakes. Nevertheless, the process of capturing, storing, reviewing and reusing LL often remains suboptimal. Despite the potential for rich knowledge capture, lessons are often documented as simple, line-item statements devoid of context. Findings from an empirical investigation across four cases revealed a range of reasons related to the perceived quality, process and visibility of LL that lead to their limited use and application. Drawn from the cross-case analysis, this paper investigates an integrated approach to LL involving the use of a collaborative Web-based tool, which is easily accessible, intelligible and user-friendly, allowing more effective sharing of project knowledge and overcoming existing problems with LL.

The construction of social identity in newly recruited nuclear engineering staff: A longitudinal study

Abstract This study examines the process by which newly recruited nuclear engineering and technical staff came to understand, define, think, feel and behave within a distinct group that has a direct contribution to the organization׳s overall emphasis on a culture of reliability and system safety. In the field of organizational behavior the interactive model of social identity formation has been recently proposed to explain the process by which the internalization of shared norms and values occurs, an element critical in identity formation. Using this rich model of organizational behavior we analyzed multiple sources of data from nine new hires over a period of three years. This was done from the time they were employed to investigate the construction of social identity by new entrants entering into a complex organizational setting reflected in the context of a nuclear facility. Informed by our data analyses, we found support for the interactive model of social identity development and report the unexpected finding that a newly appointed member׳s age and level of experience appears to influence the manner in which they adapt, and assimilate into their surroundings. This study represents an important contribution to the safety and reliability literature as it provides a rich insight into the way newly recruited employees enact the process by which their identities are formed and hence act, particularly under conditions of duress or significant organizational disruption in complex organizational settings.

ERP stakeholders’ perceptions of data quality and utility

While data quality has been identified as a critical factor associated with enterprise resource planning (ERP) failure, the relationship between ERP stakeholders, the information they require and its relationship to ERP outcomes continues to be poorly understood. Applying stakeholder theory to the problem of ERP performance, we put forward a framework articulating the fundamental differences in the way users differentiate between ERP data quality and utility. We argue that the failure of ERPs to produce significant organisational outcomes can be attributed to conflict between stakeholder groups over whether the data contained within an ERP is of adequate ‘quality’. The framework provides guidance as how to manage data flows between stakeholders, offering insight into each of their specific data requirements. The framework provides support for the idea that stakeholder affiliation dictates the assumptions and core values held by individuals, driving their data needs and their perceptions of data quality and utility.