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The purpose of this paper is to determine the significant variables leading to successful implementation of enterprise resource management (ERM) and its predecessor concepts of enterprise resource planning, supply chain planning, electronic commerce, and radio frequency identification systems. An implementation roadmap is presented using four stages for implementing ERM systems: planning, development, implementation, and testing. The roadmap indicates when and where the significant success variables would appear and how a firm might manage the implementation process.

In the research, the key success criteria and key implementation drivers uncovered by literature, case studies, and interviews were used. A survey instrument was constructed and the survey hosted on a web site where practitioners from industry were invited to supply opinions. The data were analyzed by using correlation models and one‐way analysis of variance (ANOVA) to develop cause‐effect diagrams (CE) for overall ERM systems and each component of ERM. Based on the controlled error of the ANOVA process, the CE diagram was used to depict the degree to which variables influence implementation success.

The research results have helped uncover the key significant variables that contribute to successful ERM implementation.

The proposed implementation roadmap indicates when and where the significant success variables would appear and how a firm might manage the implementation process.

The purpose of this paper is to investigate factors that influence effective workplace designs for knowledge workers.

During spring 2016, the employees in a large institution for research and higher education, a large consultancy company and a medium-sized consultancy company (in total 4367 employees) in Norway received invitations to participate in an anonymous online survey about workplaces and facilities. In all, 1,670 employees answered the survey (38.2 per cent response rate). The data have been analyzed with IBM SPSS version 23, among others through use of exploratory factor analysis and two-way ANOVA.

Most respondents at the institution for research and higher education have cell offices. Most respondents in the two consultancy companies have open and flexible offices. This paper indicate the respondents’ preferences or perception of their workstation and the workplace’s fit for their tasks is affected both by the respondents’ type of office and how much time they spend at their workstation during the week. There are also possible age or generation effects.

One methodical weakness in the present paper is that two-way ANOVA has been applied on survey data. Experiments are usually arranged to provide almost equal numbers of observations in each category. This is usually not possible with survey data. However, despite this weakness, the present paper provides several findings that challenge some of the workplace research’s taken for givens.

The present paper indicates that facility managers and others responsible for office and workplace design are advised to take the employees’ tasks and work patterns into consideration when designing workplaces and providing offices and workstations to their end-users. The present paper also indicates that employees require different kinds of support facilities and services depending on what kind of offices and workplaces they have.

This is a large N empirical study among knowledge workers in three organizations, one public administration and two private enterprises. The present paper indicate that provision of offices and workstations with supporting facilities should be differentiated according to the end-users’ work tasks and work patterns.

The complex interaction of politics and the economy is a critical factor for the sustainable growth and development of the construction sector (CNS). This study aims to investigate the effects of type of political administration including democracy and military on the performance of CNS using the Nigerian Construction Sector (NCS) as a case study.

A 48 year (1970–2017) time series data (TSD) on the NCS and the gross domestic product (GDP) based on 2010 constant USD were extracted from the United Nations Statistical Department database. Analysis of variance (ANOVA) and analysis of covariance (ANCOVA) models were used to analyze the TSD. The ANCOVA model includes the GDP as correlational variable or covariate.

The estimates of the ANOVA model indicate that democratic administration is significantly better than military administration in construction performance. However, the ANCOVA model indicates that the GDP is more important than political administration in the performance of the CNS. The study recommends for a new national construction policy, favourable fiscal and monetary policy, local content development policy and construction credit guaranty scheme for the rapid growth and development of the NCS.

Hitherto, little is known about the influence of political administration on the performance of the CNS. This study provides empirical evidence from a developing economy perspective. It presents the relationships and highlights recommendations for driving growth in the construction industry.

The purpose of this paper is to analyse insidership vs outsidership, enriching the revisited Uppsala model with the resource-based view, transaction cost economics and internalisation theory. The authors also address empirical gaps affecting the role of dyadic business relationships (BRs) (customers/suppliers/research institutions/competitors) and business networks and their effect on international performance. Finally, the authors research whether insiders’ firm-specific advantages have a stronger effect on international performance than outsiders’.

The authors work with an unbalanced panel data set of 14,231 firm-observations (period: 2000-2010). First, the author use ANOVA models (with pooled and panel data) in order to test the Uppsala basics. Second, the authors refine the research through dynamic Tobit models.

The authors find that insiders perform significantly better than outsiders. When analysing the impact on international performance, the authors confirm that not only do dyadic BRs with customers or suppliers have a positive effect, but so do BRs with research institutions; however, business networks with customers and suppliers have a negative impact. Finally, when testing interactions, the results point at technological skills as an alternative means to overcome the liability of outsidership.

Prior studies on this topic have been broadly focused on testing the original Uppsala (1977) model. However, the authors advance it by reconciling the revisited Uppsala (2009) model with the main international business theories as well as testing and refining its content in line with Johanson and Vahlne’s guidelines.

The purpose of this paper is to identify the critical parameters that influence ball grid array and chip size package fatigue life in a random vibration environment by using a design of experimental (DOE) approach using simulation results.

The use of DOE and analysis of variation to identify the critical parameters and a response surface to generate a functional form for global modeling would be determined. Once the global modeling’s functional form was known, it can be used as boundary condition, which would be input to a local model. Knowing the critical stress, one would estimate the fatigue life from a damage model. It is the curvature of the printed wiring board in the region of the component of interest that is driving the component’s solder joint damage. The approach in this present work involves global-local modeling approaches. In the global model approach, the vibration response of the printed circuit board (PCB) will be determined.

This global model will give the response of the PCB at specific component locations of interest. This response is then fed into a local stress analysis for accurate assessment of the critical stresses in the solder joints of interest. The stresses are then fed into a fatigue damage model to predict the life.

The analysis proposed in this paper uses a failure type approach to damage analysis and involves global and local model approaches.

The purpose of this paper is to explore influential factors of global broadband adoption by examining adoption factors – such as platform competition, information and communication technology (ICT) use, content, broadband speed, income, population density, education, price, and local loop unbundling (LLU).

The paper examines influential factors of global broadband adoption; it also employs regression analysis and one‐way ANOVA (Analysis of Variance). A total of 110 observations were employed for multiple regression analysis and 159 observations were used for one‐way ANOVA.

The findings in the paper show that platform competition, LLU, broadband speed, information and communication technology use, and content contribute to global broadband adoption. The impacts of platform competition are strong when market share of dominant technology and non‐dominant technology is similar.

The main findings of this paper suggest policy and strategy implications to policy‐makers and broadband service providers. This is unsponsored research that adds to the growing scholarship addressing broadband deployment factors on a comparative, international level.

The purpose of this paper is to examine police use of force using individual, contextual, and police training factors, expanding prior research by including multiple police agencies in the sample, thus producing research findings that can be more easily generalized.

The data for the current study were derived from several primary sources: the Interuniversity Consortium for Political and Social Research (ICPSR). Census, Uniform Crime Reports (UCR), Bureau of Labor Statistics (BLS), and 1997 Law Enforcement Management and Administrative Statistics (LEMAS).

Among individual level variables, age and arrestee's resistance were significant explanatory factors. Violent crime rate and unemployment rate were significant factors as the neighborhood contextual variables. Finally, in‐service training was a significant organizational‐level explanatory factor for levels of police use of force.

The paper bridges the gap in research between contextual factors and police use of force. It also deepens our understandings of the association between organizational factors and use of force by incorporating police training into the analytical model.

The empirical modelling of major rapid prototyping (RP) processes such as fused deposition modelling (FDM), selective laser sintering (SLS) and stereolithography (SL) has attracted the attention of researchers in view of their contribution to the overall cost of the product. Empirical modelling techniques such as artificial neural network (ANN) and regression analysis have been paid considerable attention. In this paper, a powerful modelling technique using genetic programming (GP) for modelling the FDM process is introduced and the issues related to the empirical modelling of RP processes are discussed. The present work aims to investigate the performance of various potential empirical modelling techniques so that the choice of an appropriate modelling technique for a given RP process can be made. The paper aims to discuss these issues.

Apart from the study of applications of empirical modelling techniques on RP processes, a multigene GP is applied to predict the compressive strength of a FDM part based on five given input process parameters. The parameter setting for GP is determined using trial and experimental runs. The performance of the GP model is compared to those of neural networks and regression analysis.

The GP approach provides a model in the form of a mathematical equation reflecting the relationship between the compressive strength and five given input parameters. The performance of ANN is found to be better than those of GP and regression, showing the effectiveness of ANN in predicting the performance characteristics of the FDM part. The GP is able to identify the significant input parameters that comply with those of an earlier study. The distinct advantages of GP as compared to ANN and regression are highlighted. Several vital issues related to the empirical modelling of RP processes are also highlighted in the end.

For the first time, a review of the application of empirical modelling techniques on RP processes is undertaken and a new GP method for modelling the FDM process is introduced. The performance of potential empirical modelling techniques for modelling RP processes is evaluated. This is an important step in modernising the era of empirical modelling of RP processes.

Describes statistical methods applied to three or more sample groups. Discusses analysis of variance in parametric forms and the requirement for experimental design control before its application.

This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups.

An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic data set. The three approaches were compared by results and violations of statistical assumptions.

Through the illustrative example, it is demonstrated how different statistical approaches can produce varied results. Only PSA mitigated pre-existing group differences without violating the assumption of independence.

This paper attempts to answer calls in the literature for more robust statistical methodologies to better inform human resource development practice and theory.