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The purpose of this paper is to draw on resource orchestration theory (ROT) and resource advantage theory (RAT) to develop a measurement scale for supply chain competitive advantage (SCCA) as a second-order construct with the dimensions of agility, adaptability and alignment (triple-A).

A survey research design is adopted to collect primary and secondary data from 182 international firms. The paper utilizes a scale development procedure to develop a measurement instrument and assess its psychometric properties. The scale’s predictive validity is tested using both subjective and objective data. Additionally, the simultaneous effect of triple-A is tested using latent congruent modeling.

Drawing upon ROT and RAT, this study introduces SCCA as a second-order construct composed of SC agility, adaptability and alignment. In addition, the findings show that an SCCA has a direct and positive impact on firms’ financial and market performance.

Existing literature indicates that competition has shifted from inter-firm to inter-SC. To account for this change in competition level, past studies have suggested various capabilities that SCs must possess to offer a competitive advantage, such as triple-As. However, drawing upon RAT and ROT, the authors argue that the SCCA construct accounts for sources of advantage in both the resource side and the demand side. The authors further assert that possessing supply chain resources (i.e. agility, adaptability, alignment as disparate resources) is not sufficient to create advantage but the resources must be orchestrated to create SCCA (i.e. the combination of agility, adaptability and alignment).

This study examines the impact of knowledge management capabilities on agility, adaptability and alignment (triple-A), drawing upon the nexus of the knowledge-based view and dynamic ambidexterity in the context of manufacturing industry in the USA. It also assesses the performance outcomes of triple-A capabilities in terms of operational and relational performance.

Path analysis was performed in this empirical study in the manufacturing industry.

The results show that knowledge management capabilities are conducive to the development of triple-A capabilities, which in turn lead to the improvement of operational and relational performance.

This study is grounded in the marriage of the knowledge-based view and dynamic ambidexterity to assess the combinative impact of knowledge management capabilities of knowledge acquisition and sharing through absorptive and desorptive capacities on agility and adaptability through knowledge exploration and alignment by knowledge exploitation in the pursuit of triple-A capabilities. This study unentangles the linkage between knowledge management capabilities and triple-As by theorizing the connection between absorptive/desorptive capacity and exploration/exploitation in terms of responsive and efficient supply chain respectively.

Examines the impact of the intensity level of computer‐based technologies (CBTs) on quality. The intensity level of CBTs is empirically‐based. The main thrust of the intensity level of CBTs is fourfold. First, the technology must, intuitively, exist. Second, it must be integrated with other available technologies. Third, it must be utilized to a certain extent. Finally, it must have been used long enough to produce synergistic results. Determines whether there are differences in quality among firms with different intensity levels of CBTs. The analysis was based on data collected from 165 manufacturing firms in three industry groups in the USA. These are industrial machinery equipment, electronic and electric machinery equipment, and transport equipment. Descriptive statistics show the following: (1) the level of technology integration is low; (2) the level of programmable automation is also low; (3) most of the CBTs are used as stand‐alone technologies; and (4) most of the CBTs are used in the early stages of designing the product. The results also suggested that differences in quality exist among groups with different intensity levels of CBTs. These findings have many implications for both practitioners and academicians. For practitioners, the intensity level of CBTs, as operationalized here, can be used by manufacturing firms as a vehicle to benchmark their performance against that of their competitors. For academicians, introduces a new measure for operationalizing the intensity level of CBTs. Also discusses other implications.

Drawing on configuration theory and adopting a holistic perspective, the authors aim to explore strategic supply chain elements' interaction with internal and external contextual conditions. Specifically, they evaluate multivariate co-alignment of supply chain's capabilities (agility, adaptability, alignment), adhocracy organizational structure and environmental uncertainty (dynamism, munificence and complexity) that lead to superior performance outcomes (supply chain cycle time, financial performance, market performance).

A survey research design is adopted to collect primary and secondary data from 182 international firms. Cluster analysis and profile deviation techniques are employed first to derive a taxonomy of strategic supply chains and then examine multivariate co-alignment.

The analysis reveals that four groups of triple-A supply chains could emerge. It is found that strategic supply chains exhibit a flexible/organic/fluid organizational structure and a high level of triple-As in their processes. These supply chains perform superior to a higher level of environmental complexity, munificence and dynamism.

This study's results provide insights for practitioners by informing their investment decisions for developing strategic supply chains. Specifically, this research highlights the contextuality of triple-A supply chains and offers best practices to capitalize on strategic supply chains.

Executives in organizations require a holistic understanding of various elements to ensure that the organizational system as a whole performs effectively. This research offers insights into the interdependencies of triple-A supply chains with other organizational and external environmental elements. Noteworthy implications for scholarship in operations/supply chain management and supply chain practitioners are presented.

Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data.

This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star/snowflake schemas and materializes relevant triples as fact and dimension tables for online analytical processing (OLAP).

The applicability of H-SPOOL is evaluated using exiting LD data sets on the Web, and H-SPOOL successfully processes the LD data sets to ETL (Extract, Transform, and Load) for OLAP. Besides, experiments show that H-SPOOL reduces the number of downloaded triples comparing with existing approach.

H-SPOOL is the first work for extracting OLAP-related information from SPARQL endpoints, and H-SPOOL drastically reduces the amount of downloaded triples.

This paper aims to propose a characteristic stabilized finite element method for non-stationary conduction-convection problems.

To avoid difficulty caused by the trilinear term, the authors use the characteristic method to deal with the time derivative term and the advection term. The space discretization adopts the low-order triples (i.e. P₁-P₁-P₁ and P₁-P₀-P₁ triples). As low-order triples do not satisfy inf-sup condition, the authors use the stability technique to overcome this flaw.

The stability and the convergence analysis shows that the method is stable and has optimal-order error estimates.

Numerical experiments confirm the theoretical analysis and illustrate that the authors’ method is highly effective and reliable, and consumes less CPU time.

Purpose – To investigate the potential of the semantic web as a source of information about social networks within academia, as well as more widely for webometric investigations.

Methodology – The functionality of five semantic search engines were analyzed to determine their suitability for webometric investigations, with the most suitable, Sindice.com, then being used to investigate the use of Friend of a Friend (FOAF) within UK academic web space.

Findings – In comparison to the web of documents, the semantic web is still a small part of online content. Even the well-established FOAF social vocabulary was not found on the majority of academic web sites, let alone being found to represent the majority of academics, and provided little indication of social networks between institutions. Nonetheless from a webometric perspective the study does show the potential of a semantic web for a far wider range of webometric investigations, and demonstrates that, unlike the traditional web, there are currently useful tools available.

Implications – Having established that there are appropriate tools available for webometric investigations of the semantic web, and acknowledging the potential of the semantic web for far more detailed webometric investigations, there is a need for additional studies to determine the specific strengths and limitations of the tools that are available, and investigate those areas where webometric investigations can provide the most useful insights.

Originality/value – The research applies established webometric methodologies to the social semantic web, demonstrating the potential of a whole new area for future webometric investigation.

This article discusses credit migration of diversified loan pool securitizations, as evidenced by the ratings transitions of mortgage‐backed securities (MBS) and asset‐backed securities (ABS). The authors contrast the ratings (i.e., credit) stability of MBS and ABS relative to ratings migration of general obligation corporate credit. They also use holding period returns to compare the total return portfolios of MBS/ABS to portfolios of senior unsecured corporate obligations.

Drawing on complementarity theory, this paper aims to examine the type and effect of interdependencies/interaction (i.e. complementarity or substitutability) between the supply chain capabilities of agility, adaptability and alignment.

A survey research design is adopted to collect primary and secondary data from 182 international firms. The complementarity (or substitutability) of three As (agile, adaptable and aligned) were analyzed in three-way and pairwise interactions; both, correlation and performance differences methods of testing the type of interactions among the system’s elements were used. Supply chain-centric and firm-centric performance metrics were used to examine the interaction types.

The study did not find empirical evidence of three-way complementarity between the three As. However, this paper did find evidence of complementarity in bivariate interactions for alignment and adaptability. Moreover, in the performance difference method, the study found a substitute relationship between all pairs of As.

The findings related to the substitutability between the three As offer managers guidance on how to allocate their limited resources to avoid unnecessary over-or under-investing in either one of the three As.

This study helps refine prior findings related to the three As by offering evidence that firms can still achieve their performance-related goals with reduced investment commitments by taking advantage of the substitutability relationship existent between these capabilities. That is, instead of concomitantly developing all three As as past studies have suggested, managers can use the findings to determine how to prioritize their resource allocation better. Furthermore, understanding the actual interaction among the supply chain variables generally provide insights for designing the supply chain, change management in the supply chain, developing supply chain strategy and adopting best practices in the supply chain.

With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources.

First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree.

The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query.

Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.