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The purpose of this paper is to explore the ways in which various dimensions of supply chain performance (SCP) can be improved through increased levels of process orientation across different core operational processes. This study aims to provide simple guidelines which are practical for business managers.

A conceptual model was developed based on the literature review and it was tested using an empirical study. Various factor analysis techniques are used to construct different components of the research model and test the hypotheses.

This study provides two main categories of findings. First, based on the exploratory analysis several constructs were developed. Second, using structural equation modeling the relationships among the constructs were examined. The findings suggest that managers need to take a targeted approach in increasing the levels of process orientation in order to achieve particular SCP goals.

The result of this study is not indented to be generalized to all businesses; however, the methodology is flexible enough to be utilized in different industries and business scenarios.

The present study provides specific recommendations for business managers seeking to enhance various aspects of their organizational SCP. The research model can be used for future empirical as well as case studies.

This is the first comprehensive empirical study that separately measures business process orientation with respect to four core supply chain processes (planning, sourcing, making, and delivering) and assesses the impact of each core process on various dimensions of supply chain performance.

While a global supply network can provide stability to address localized interruptions, however, the recent global pandemic materialized many concerns and risks associated with the global supply network. Considering the short-term and long-term effects of changes in the global supply chain, this research explores how the location characteristics of the firms across the supply chain affect their performance.

Using the mined data from five tiers of the backward supply chain of medical equipment, the authors constructed a large supply chain network consisting of close to 160,000 dyadic connections. The authors used various network centrality and clustering algorithms to measure the influence of each firm across the supply chain structure. Furthermore, the authors ran a scenario to simulate the elimination of Chinese firms from the global supply chain and recalculated all centralities. Regression analysis was used to measure the effect of supply chain network centralities on firms' performance across the supply chain with and without Chinese firms.

The complexity of global purchasing across global tiers of supply networks had been recognized as a source of uncertainty before the COVID-19 pandemic. This pandemic was the black swan that the medical supply chain professionals had noted its threat in recent years. While a global supply network can provide stability to address localized interruptions, however, the recent global pandemic materialized many concerns and risks associated with the global supply network. Considering the short-term and long-term effects of changes in the global supply chain, this research explores how the location characteristics of the firms across the supply chain affect their performance.

This research has three main implications. First, it provides a benchmark for manufacturing firms and distributors around the world operating in the post-COVID-19 business environment to better understand the relationship of their supply chain strategy and firms' financial performance. Second, investors and asset managers can evaluate their portfolios in light of the changing relationship as a result of possible protectionism initiatives. Finally, policymakers can apply the research methodology of this work in various industries while reevaluating post-COVID-19 international relations and trades policies at the firm, industry and country levels.

Policymakers working on global connection can utilize the outcome of this research to explore the consequences of local and global policies on trade patterns, organizational performance as well as individuals' movements. Another implication of this study for policymakers is that it provides a powerful simulation and analytical tool to launch or combat the global ruptures, including trade wars and natural disasters stemming from natural events (e.g. climate change) and human-made events (e.g. wars, supply-chain interruptions, sanctions).

To the best of our knowledge, this is the first large-scale empirical study that measures the effect of supply chain structure across multiple (five) tiers of the global supply chain on firms' performance. The present study uses the original supply chain network data mined by the authors from financial publications.

The purpose of this paper is to investigate the role of Business Process Orientation (BPO) at intra- and inter-organizational levels in various aspects of organizational performance.

A comprehensive research model is developed based on the review of literature. The research model is later examined and modified based on the analysis of a sample of 3200 for-profit organizations. Factor analysis and structural equation modeling techniques are used to investigate the research questions presented in the study.

The findings of this study suggest that while higher levels of BPO at intra-organizational level provide direct financial and operational benefits for the firms in our sample. Higher levels of BPO at inter-organizational level provide direct customer satisfaction benefits as well as indirect financial and operational benefits.

Lack of sufficient previous studies and theories in this area is one of the main limitations of the study.

One of the important managerial implications of the present study is that organizations can learn about the types of benefits that they may expect to gain through a higher level of BPO at each of the two levels of analysis in this study: intra- and inter-organizational.

The measurement models and the comprehensive structural model are the main original contributions of this study. As far as can be determined, this is the first study that measures BPO at intra- and inter-organizational levels with respect to suppliers and customers, in addition to investigating the role of BPO on various aspects of organizational performance indicators through a large scale empirical study.

This study seeks to explore the role of process orientation (PO) in organizations that go through a transition in implementing enterprise systems (ESs).

Based on an empirical survey of 3,000 large Canadian and US firms, this study investigates the role of PO in various aspects of ES implementation. Exploratory factor analysis is conducted using SPSS software to identify indicators and factors of measuring PO and various aspects of ES implementation. Furthermore, the LISREL software was used to perform the path analysis to identify the role of PO.

The results of the analysis strongly suggest that the PO levels at three phases of ES implementation are independent and, hence, require separate measurement. In addition, two research models are employed to examine 14 hypotheses associated with the role of PO in ES implementation. The findings indicate that process‐oriented organizations in our sample are more successful in ES implementation and have faced fewer challenges in the transition process.

This study unveils the role of PO in successful ES implementation. The champions of transition pay special attention to PO throughout the ES implementation. The findings reveal that under certain conditions PO can hinder or support the ES implementation in organizations.

This is the first study that measures PO at three phases of ES implementation. Moreover, two research models are employed to study the research topic, namely: preliminary model, and expanded model. Measurement of PO at three stages of transition provides a unique perspective to evaluate the effect of PO in organizations.

In the past few years, process orientation (PO) as an integral part of enterprise system (ES) implementation has been the center of attention among practitioners and academics. The purpose of this paper is to shed light on the role of PO in ES implementation through an empirical study of Canadian and US firms.

A comparative analysis of ES implementation was performed based on the data collected from a sample of large Canadian and US firms. Exploratory factor analyses were conducted to identify the factors associated with constructs of the research model. Moreover, path analysis approach was employed to conduct comparative analysis across the two samples.

The findings indicate that PO significantly reduces the challenges of ES implementation. Moreover, PO has been shown to have a positive effect on the successful implementation and utilization of ES under certain conditions. However, the level of PO at different phases is observed to have diverse effects on different aspects of ES implementation as a result of opposite forces of change. In addition, the path analysis confirms the validity of measurement of PO at three phases of ES implementation.

No database of managers who have been involved in all three phases of ES implementation exists; hence, the respondents are asked to answer the questionnaire only if they are involved in all three phases of ES implementation. This places a limitation on the respond rate.

This paper is the first paper that measures PO at three phases of ES implementation and explores the effect of PO on different dimensions of ES implementation. This approach provides a novel insight into understanding of the role of PO in ES implementation. This paper offers two major contributions toward a further understanding of the business processes in organizations. The first contribution of this paper is the development of measurement systems for assessing the level of PO and various dimensions of ES implementation. The second major contribution of this paper is unveiling the role of PO in ES implementation through the comparative analysis across Canadian and US firms.

Though many studies and reports have been published about the scale of identity fraud (IDF), no work has been done on developing models to measure IDF. The purpose of this paper is to propose a measurement model for IDF and test the validity of that measurement model.

After providing a background on the concepts of IDF, the paper discusses the related term, identity theft. Next, a measurement model is developed, based on the current practice of measurement of IDF in four countries. Exploratory factor analysis (EFA) is used in identifying the indicators and factors of IDF. After the EFA is conducted, confirmatory factor analysis is employed to test the validity of the measurement model. These tests are conducted using the data collected from Canadian financial institutions.

The review of the current empirical studies suggests that IDF should be assessed using a measurement model with 33 indicators to measure five factors of IDF. However, the analysis of Canadian financial institutions suggests that a measurement model that includes 27 indicators and four factors is most appropriate for the data.

The measurement model developed in the present paper is based on an examination of a sample of financial institutions in Canada. Hence, the results of this paper cannot be generalized to organizations in other sectors of the economy. Further studies in other sectors of the economy are required to identify industry‐specific measurement model.

This paper is the first approach toward developing a model for measuring IDF.

This paper is the first study that attempts to scientifically identify and validate a measurement system in the area of IDF.

This paper aims to investigate empirically how broadband has been implemented at the business level and what are the potential adoption benchmarks. Several recent studies have called for the development of frameworks of broadband adoption, particularly at the business level, to help policy makers, communities and businesses with their strategic decision-making process.

This paper opens the discussion by presenting concerns and challenges of Internet adoption. Internet adoption is viewed as the current challenge facing businesses, communities and governments. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) techniques are used to create, analyze and develop Internet adoption models.

Based on the Internet usage data from a number of states across the USA, measurement models are developed using EFA and CFA. The findings indicate that for our sample, a three-factor model is the most appropriate for the representation of Internet adoption in the tourism sector, while a five-factor model can best describe Internet adoption in the sample of manufacturing organizations.

The availability of data on Internet usage at the business/organizational level is one of the main constraints. Industry/community-specific data can also provide valuable insights about the Internet adoption and support the development of industry/community-specific adoption models.

The findings and the employed research method can be used by businesses, communities and government managers and policy makers as benchmarks to examine broadband adoption based on gap-opportunity criteria.

This is the first study that provides Internet adoption models based on an empirical study at the business level. The benefits of broadband Internet have been investigated by many researchers in the past decade. There seems to be a consensus among practitioners and scholars about the role of broadband Internet in gaining competitive advantage. However, there have not been any previous studies that investigate how broadband has been implemented and what the potential adoption benchmarks at the business level are.