A NEW CONCEPTUALISATION OF DESIGN SCIENCE RESEARCH FOR DSS DEVELOPMENT RESEARCH

Despite a well-established research tradition, the field of Decision Support Systems (DSS) suffers from a lack of practitioner relevance. DSS researchers have comprehended the emergence of Design Science Research (DSR) for the issue as it provides support to improve the behavioral aspect of design. However, conceptualizations for DSR as the common approach to conducting DSS research have not been materialized to address the relevance issues. In the paper extending an existing conceptualization, we introduce a new DSR view for DSS development. The view incorporates design dimensions related to DSS design, such as professional value, interaction, intentions, practices, and problem-solving. We developed the DSR view from an action design research approach conducted through a well-defined framework for developing a generic DSS solution. The view represents the importance of practitioner’s centric DSR to better address practitioner’s relevance issues in DSS design

Competitive intelligence practice in liquor retailing: evidence from a longitudinal case analysis

Competitive intelligence (CI) is a vital tool for any company to survive and remain competitive in today’s hypercompetitive and uncertain business environment. The purpose of the current study is to investigate the use of competitive intelligence (CI) in liquor retailing in the USA. An exploratory single longitudinal case study was performed through observation and semi-structured interviews plus examining documents from secondary sources in two phases. Content analysis was used for the data analysis. Regardless of the small size of the company, the owner has an active attitude towards monitoring competition by using various sources of information and converting it into intelligence for making sound decisions for both short-term and long-term competitiveness. Also, the central role of the owner in the CI process has been verified. This study responds to calls for more case studies in the field and is the first one to explore CI in the liquor retailing ecosystem by using a longitudinal case study. In general studies of CI in retailing are limited. It has clear value to CI practices for retailers in the US and in general

A Look Toward the Future: Decision Support Systems Research is Alive and Well

This commentary examines the historical importance of decision support to the information systems (IS) field from the viewpoint of four researchers whose work spans the several decades of decision support systems (DSS) research. Given this unique “generational” vantage point, we present the changes in and impact of DSS research as well as future considerations for decision support in the IS field. We argue that the DSS area has remained vital as technology has evolved and our understanding of decision-making processes has deepened. DSS work over the last several years has contributed both breadth and depth to decision-making research; the challenge now is to make sense of it all by placing it in an understandable context and by applying our analysis to the relevant issues looming in the future. One major outcome of this commentary is the identification of future trends in DSS research and what the users of these new DSS outlets can learn from the past. Trends include the increasing impact of social and mobile computing on DSS research, as well as knowledge management DSS and negotiation support systems that shift the focus to delivering more customer-centric and marketplace support

Kuntien tiedolla johtaminen : Kunnallishallinnon tietojärjestelmäratkaisun hankinnan vaatimukset ja esteet

Kuntien toimintaympäristön epävarmuuden lisääntyessä kunnat tarvitsevat päätöksenteon tueksi entistä enemmän tietoa toiminnastaan. Vaikka tehokkaan päätöksenteon edellytys ovat sujuvat informaatiovirrat prosessien välillä sekä huolellinen, tietoon perustuva päätösten valmistelu, kunnilla ei ole usein käytössä riittävästi relevanttia, luotettavaa tai vertailukelpoista tietoa kunnan johtamisen ja päätöksenteon tarpeisiin. Jotta päätöksenteossa voidaan reagoida muutoksiin nopeasti, päätöksenteon tueksi tarvitaan tietojärjestelmäratkaisuja, joiden avulla eri lähteistä tulevaa tietoa voidaan yhdistää tulevaisuuden ennakoimiseksi. Vaikka tiedolla johtamisen tarve nyky-ympäristössä on selvä, monet kunnat eivät ole ottaneet käyttöön kuntien tarpeisiin suunniteltuja tiedolla johtamisen järjestelmäratkaisuja. Tästä syystä tämä tutkimus tarkastelee, mikä estää kuntia hankkimasta tai ottamasta käyttöön kunnallishallinnon tiedolla johtamisen tarpeisiin kehitettyjä järjestelmäratkaisuja ja mitkä ovat kunnallishallinnon näkökulmasta kuntien tiedolla johtamisen järjestelmäratkaisun vaatimukset. Tutkimuksessa noudatetaan induktiivista ankkuroidun teorian (grounded theory) lähestymistapaa, jonka mukaisesti tutkimuksen kirjallisuusintegraatio on toteutettu vasta aineiston keräyksen jälkeen. Tutkimuksen kirjallisuusintegraatiossa hyödynnetään teoreettista otantaa, jossa kirjallisuusotanta koostuu tutkimuksen kannalta olennaisesta tiedolla johtamisen järjestelmiä sekä järjestelmien hankintaa käsittelevästä kirjallisuudesta. Empiirisen aineiston analyysin ja kirjallisuusintegraation pohjalta tutkimuksen lopputuotteena muodostuu kuntien tiedolla johtamisen tietojärjestelmäratkaisujen kehittämisen viitekehys, jonka avulla kuntien tiedolla johtamisen järjestelmien kehittämisen eri osapuolien rooleja ja vastuita voidaan tunnistaa jatkossa helpommin. Tutkimuksen tulosten mukaan tiedolla johtamisen järjestelmien pohjainfrastruktuuri on kunnissa puutteellinen ja kuntien tiedolla johtamisen järjestelmäympäristö on samalla tasolla kuin yksityisen sektorin suuryrityksissä 80–90-luvuilla. Puutteellisen pohjainfrastruktuurin vuoksi kunnilla ei vielä ole valmiuksia ottaa käyttöön nykyaikaisia tiedolla johtamisen järjestelmiä. Niin kauan kuin kunnissa ei ole järjestelmiä, jotka tuottaisivat riittävästi tietoa johtamisen tarpeisiin, kuntia ei käytännössä voida johtaa tiedolla. Järjestelmien käyttöönottoa ja hankintaa estävät myös vallalla olevat asenteet, toimintakulttuuri sekä käytössä olevat järjestelmät, teknologiat ja prosessit. Tulosten valossa näyttää siltä, että kuntien tiedolla johtaminen on yleisesti huonossa tilassa. Tutkimuksen pohjalta voidaan myös todeta, että siinä missä yksityisellä sektorilla puhutaan business intelligence -järjestelmistä julkisella sektorilla Suomessa puhutaan tällä hetkellä tiedolla johtamisesta

Design of Data-Driven Decision Support Systems for Business Process Standardization

Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”. Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. The thesis conducts the DSR projects at an industry partner within the context of a BPS and SAP S/4 HANA transformation program at a global manufacturing corporation. DSR project 1 designs a data-driven “Business Model Mining” system that automatical-ly “mines” BMs from data in application systems and represents results in an interactive “Business Model Canvas” (BMC) BI dashboard to comprehend BM-related BPS con-tingency factors. The project derives generic design requirements and a blueprint con-ceptualization for BMM systems and suggests an open, standardized reference data model for BMM. The project implements the software artifact “Business Model Miner” in Microsoft Azure / PowerBI and demonstrates technical feasibility by using data from an educational SAP S/4 HANA system, an open reference dataset, and three real-life SAP R/3 ERP systems. A field evaluation with 21 managers at the industry partner finds differences between tool results and BMCs created by managers and thus the po-tential for a complementary role of BMM tools to enrich the comprehension of BMs. A further controlled laboratory experiment with 142 students finds significant beneficial impacts on subjective and objective comprehension in terms of effectiveness, efficiency, and relative efficiency. Second, DSR project 2 designs a data-driven process mining DSS “KeyPro” to semi-automatically discover and prioritize the set of BPs occurring in an organization from log data to concentrate BPS initiatives on important BPs given limited organizational resources. The project derives objective and quantifiable BP importance metrics from BM and BPM literature and implements KeyPro for SAP R/3 ERP and S/4 HANA sys-tems in Microsoft SQL Server / Azure and interactive PowerBI dashboards. A field evaluation with 52 managers compares BPs detected manually by decision-makers against BPs discovered by KeyPro and reveals significant differences and a complemen-tary role of the artifact to deliver additional insights into the set of BPs in the organiza-tion. Finally, a controlled laboratory experiment with 30 students identifies the dash-boards with the lowest comprehension for further development. Third, OCT requires organizations to select a standard BP design that matches contin-gencies. Thus, DSR project 3 designs a process mining DSS to select a standard BP from a repository of different alternative designs based on the similarity of BPS contin-gency factors between the as-is process and the to-be standard processes. DSR project 3 thus derives four different process model variants for representing BPS contingency factors that vary according to determinant factors of process model comprehension (PMC) identified in PMC literature. A controlled laboratory evaluation with 150 stu-dents identifies significant differences in PMC. Based on laboratory findings, the DSS is implemented in the BPM platform “Apromore” to select standard BP reference mod-els from the SAP Best Practices Explorer for SAP S/4 HANA and applied for the pur-chase-to-pay and order-to-cash process of a manufacturing company