Empirical Test Guidelines for Content Validity: Wash, Rinse, and Repeat until Clean

Empirical research in information systems relies heavily on developing and validating survey instruments. However, researchers’ efforts to evaluate content validity of survey scales are often inconsistent, incomplete, or unreported. Thjs paper defines and describes the most significant facets of content validity and illustrates the mechanisms through which multi-item psychometric scales capture a latent construct’s content. We discuss competing methods and propose new methods to assemble a comprehensive set of metrics and methods to evaluate content validity. The resulting recommendations for researchers evaluating content validity emphasize an iterative pre-study process (wash, rinse, and repeat until clean) to objectively establish “fit for purpose” when developing and adapting survey scales. A sample pre-study demonstrates suitable methods for creating confidence that scales reliably capture the theoretical essence of latent constructs. We demonstrate the efficacy of these methods using a randomized field experiment

Issues and Guidelines in Modeling Decomposition of Minimum Participation in Entity-Relationship Diagrams

The entity-relationship model has long been employed for conceptual modeling of databases. Methodologies and heuristics have been developed, both for effective modeling and for translating entity-relationship models into relational models. One aspect of modeling that is often overlooked in design methodologies is the use of optional versus mandatory participation (i.e., minimum participation) on the development of relational databases. This tutorial complements existing instructional material on database design by analyzing the syntactic implications of minimum participation in binary, unary, and n-ary relationship sets and for the special case where the E-R diagram depicts a database where 3NF is not in BCNF. It then presents design modeling guidelines which demonstrate that (1) for binary 1:1 and 1:M relationship sets, the presence of optional participation sometimes means that the relationship set should be represented in the relational model by a separate relation, (2) unary relationship sets cannot have a (1,1) participation, (3) n-ary relationship sets that have a (1,1) participation can be simplified to be of lower connectivity, and (4) decomposition is not a substitute for normalization. Illustrative examples and modeling guidelines are provided

Discovering and Transforming Exhaust Data to Realize Managerial Value

“Exhaust data” is “extra data” or “left over” data from “core data” digital transactions collected either intentionally or unintentionally but for which there is no initial, specific purpose for its collection. In this paper, we differentiate core data from exhaust data, define and describe exhaust data, and propose how to turn it into core data to provide value for firms. We present a framework for discovering and transforming exhaust data and apply it to four case studies involving Internet search data, accounting entries and data security, social media disclosures, and EDGAR use logs. From the cases, we extract five managerial challenges and generate five recommendations to help managers identify exhaust data applications for realizing potential value

Domain design principles for managing complexity in conceptual modeling

Complexity is a problem that can be found in many aspects of research that deals with design. In particular, complexity is found in various business processes that must be modeled and represented in a meaningful way. One of the ways to address complexity is by using decomposition, for which a number of decomposition principles have been proposed. However, there are two domain specific areas in which these principles are lacking: the scope and the context of the problem. This research addresses this problem by deriving two new principles for managing complexity, and evaluates the proposed principles through an example case to illustrate their potential use

Identifying Authorship from Linguistic Text Patterns

Research that deals with linguistic text patterns is challenging because of the unstructured nature of text. This research presents a methodology to compare texts to identify whether two texts are written by the same or different authors. The methodology includes an algorithm to analyze the proximity of text, which is based upon Zipf’s Law [47][48]. The results have implications for text mining with applications to areas such as forensics, natural language processing, and information retrieval

A Tutorial on Prototyping Internet of Things Devices and Systems: A Gentle Introduction to Technology that Shapes Our Lives

The Internet of Things, which has been quietly building and evolving over the past decade, now impacts many aspects of society, including homes, battlefields, and medical communities. Research in information systems, traditionally, has been concentrated on exploring the impacts of such technology, rather than how to actually create systems using it. Although research in design science could especially contribute to the Internet of Things, this type of research from the Information Systems community has been sparse. The most likely cause is the knowledge barriers to learning and understanding this kind of technology development. Recognizing the importance of the continued evolution of the Internet of Things, this paper provides a basic tutorial on how to construct Internet of Things prototypes. The paper is intended to educate Information Systems scholars on how to build their own Internet of Things so they can conduct technical research in this area and instruct their students on how to do the same

Research on conceptual modeling: Themes, topics, and introduction to the special issue

Conceptual modeling continues to evolve as researchers and practitioners reflect on the challenges of modeling and implementing data-intensive problems that appear in business and in science. These challenges of data modeling and representation are well-recognized in contemporary applications of big data, ontologies, and semantics, along with traditional efforts associated with methodologies, tools, and theory development. This introduction contains a review of some current research in conceptual modeling and identifies emerging themes. It also introduces the articles that comprise this special issue of papers from the 32nd International Conference on Conceptual Modeling (ER 2013).This article was supported, in part, by the J. Mack Robinson College of Business at the Georgia State University, the Marriott School of Management at Brigham Young University (EB-201313), and by the GEODAS-BI (TIN2012-37493-C03-03) project from the Spanish Ministry of Education and Competitivity

System: A core conceptual modeling construct for capturing complexity

[EN] The digitalization of human society continues at a relentless rate. However, to develop modern information technologies, the increasing complexity of the real-world must be modeled, suggest-ing the general need to reconsider how to carry out conceptual modeling. This research proposes that the often-overlooked notion of "system"should be a separate, and core, conceptual modeling construct and argues for incorporating it and related concepts, such as emergence, into existing approaches to conceptual modeling. The work conducts a synthesis of the ontology of systems and general systems theory. These modeling foundations are then used to propose a CESM+ template for conducing systems-grounded conceptual modeling. Several new conceptual modeling notations are introduced. The systemist modeling is then applied to a case study on the development of a citizen science platform. The case demonstrates the potential contributions of the systemist approach and identifies specific implications of explicit modeling with systems for theory and practice. The paper provides recommendations for how to incorporate systems into existing projects and suggests fruitful opportunities for future conceptual modeling research.We wish to thank the editor-in-chief, Carson Woo, and three anonymous reviewers for their exceptionally insightful and developmental comments. The substantial improvements that resulted from their feedback were much deeper than we usually experience in journal review processes. We wish to thank the participants of www.nlnature.com (now inactive) who contributed their sightings from 2010 to 2022. We also thank Jeffrey Parsons and Yolanda Wiersma - the co -investigators of NLNature. We are grateful to the late Mario Bunge and to Ron Weber with whom we discussed ontological ideas that inspired this paper. We also want to thank the participants and reviewers of AIS SIGSAND and ER Conference for their comments and feedback on earlier versions of this paper. This research was supported by McIntire School of Commerce, University of Virginia, J. Mack Robinson College of Business, Georgia State University, United States, and by VRAIN Research Institute of the Universitat Politecnica de Valencia and the Generalitat Valenciana, Spain under the CoMoDiD project (CIPROM/2021/023) .Lukyanenko, R.; Storey, VC.; Pastor López, O. (2022). System: A core conceptual modeling construct for capturing complexity. Data & Knowledge Engineering. 141:1-29. https://doi.org/10.1016/j.datak.2022.10206212914

EXPLORING A DOMAIN ONTOLOGY BASED APPROACH TO BUSINESS PROCESS DESIGN

Business process modeling is a critical area of business application as business processes increase in complexity and become more automated. However, little attention has been paid to the fact that business process modelers often misunderstand domain concepts or relationships due to a lack of precise domain knowledge. This semantic ambiguity problem often affects the efficiency and quality of business process modeling. To address this problem, we propose a domain ontology based approach (DOBA) to supporting business process design by capturing domain semantics with a meta model of process ontologies. DOBA provides a means to capture rich, semantic information on complex business processes, which enables the incorporation of domain specific ontologies to facilitate modeling of business processes. The validity of DOBA is demonstrated via a business case in electronic auctions. The DOBA approach represents a first step towards developing a formal methodology for ontology-based modeling and analysis in business process management