Keywords

1 Introduction

Digital technologies profoundly impact society, the economy, and daily life [1]. Digital transformation (DT), characterized by significant changes through information, computing, communication, and connectivity technologies, promises micro, meso, and macro benefits. It influences how individuals work and spend their free time [2]. At the meso level, businesses can experience improved efficiency, productivity, and revenue [3], leading to higher living standards at the macro level [3]. Organizations often face barriers when attempting to fully leverage the transformative potential of digital technologies [4]. DT encompasses integrating digital technologies, leading to socio-technical changes within organizations [1, 5]. Barriers, derived from innovation management and organizational change research, hinder or prevent DT activities [6, 7]. Barriers are factors “that can hinder or stop the successful implementation of DT” [8]. Research has predominantly focused on success factors [9]. However, since barriers are more than the mere opposite of success factors, the results cannot simply be transferred [10]. Understanding these barriers is crucial for effective implementation and requires identification, analysis, and appropriate countermeasures. Previous studies on barriers have primarily focused on digitalization rather than the broader scope of DT [11, 12]. Thus, they cannot grasp the scope and scale of DT, which requires additional in-depth research [12, 13]. Luckily, researchers are increasingly examining barriers in the context of DT. However, as this research field is increasingly growing, keeping track of the different concepts and themes is getting challenging. The growing field of barriers in DT research necessitates comprehensive exploration to capture diverse concepts and themes [4]. This study aims to identify the research streams and topics related to DT barriers. Mapping studies have arisen to help fulfill this aim. These studies aim to review “a relatively broad topic by identifying, analyzing, and structuring the goals, methods, and contents of conducted primary studies” [14]. In comparison, while a “conventional systematic literature review makes an attempt to aggregate the primary studies in terms of the research outcomes […], a mapping study usually aims […] to classify the relevant literature” [15]. Mapping studies identify broader topics such as research streams, their central subject areas, and untreated areas. [14] Mapping studies are, therefore, particularly valuable as they provide a foundation for future research [15]. Thus, our research questions are as follows: What are the research streams in the field of barriers to digital transformation? Which topics are addressed within the research streams? What research needs have been outlined within the research streams?

The study is structured as follows: First, we introduce the topic and give a brief theoretical background. After, we present the methodology of our data collection. The results comprise different clusters found in the literature and give an aggregate view of current studies and their views on future research. We close with a concluding discussion.

2 Theoretical Background

With the rapid advancements in digital technologies and their increasing impact on various aspects of society and business, the term “digital transformation” emerged. There are multiple definitions for the term available in the literature. Based on various definitions of DT, Vial constructed a conceptual definition of DT as a significant alteration of an entity’s characteristics through the integration of information, computing, communication, and connectivity technologies, utilizing new digital technologies [1]. Gong and Ribere unified DT as “a fundamental change process enabled by digital technologies that aims to bring radical improvement and innovation to an entity [e.g., an organization, a business network, an industry, or society] to create value for its stakeholders by strategically leveraging its key resources and capabilities” [16]. These definitions clearly distinguish DT from other related terms. While digitization primarily focuses on converting analog information into digital form, and digitalization pertains to the adoption of digital technologies in specific processes, DT has a comprehensive socio-technical impact on the entire organization [1, 11]. The scope of DT even goes beyond terms like IT-enabled organizational transformation (ITOT). In contrast to ITOT, DTs redefine the value proposition of organizations and create new organizational identities, while ITOT revolves around supporting the existing value proposition and reinforcing the organizations’ identity by leveraging digital technologies [12]. Consequently, regarding DT, all departments within an organization are affected and must navigate changes such as the adoption and implementation of new digital technologies, processes, structures, and potential financial barriers [4].

In recent years, many researchers in information systems have therefore studied concepts, impacts, and aspects of DT from a variety of perspectives [1]. One field of research examines the barriers to DT. However, research on barriers did not start in the context of the DT. The research field builds on areas such as innovation management [5] and organizational change [13]. Transferred from the field of innovation research, a barrier is defined as “an issue that either prevents or hampers” [14] DT activities in an organization. Due to DT, socio-technical structures previously mediated by non-digital relationships and artifacts are transformed to be mediated by digital relationships and artifacts [15]. The tensions that arise from this integration of physical and digital layers are named barriers to DT [16]. Examining barriers is essential as they differ from success factors [10]. Even though success factors are the earlier research concept, they evolved into barriers as their understanding is vital for effective implementation [13].

3 Method

Our mapping study aims to provide an overview of research on DT barriers. We combine bibliometric analysis elements with a systematic literature review to achieve this aim. Our qualitative and quantitative approaches can be divided into 3 phases.

Phase 1 (Development of the search strategy and database selection): We discussed possible search terms to identify literature related to our research topic. We decided on using the search string “(Digital Transformation) AND Barrier”, as other terms like “digitalization” do not capture the essence of the subject under investigation. The Scopus database was chosen because it contains a wide range of scientific literature and allows exporting search hits, which is necessary for our bibliometric analysis.

Phase 2 (Carrying out the literature search and selecting literature): Applying the search string, we got 374 hits in November 2022. Only English-language, peer-reviewed scientific literature from journals or conference proceedings was considered. We explicitly excluded articles whose research focus was not related to DT barriers. Following the recommendations of vom Brocke [17], we examined the hits’ titles, abstracts, and keywords to check for relevance. We identified 171 entries without relation to our subject matter, leaving us with 203 relevant publications.

Phase 3 (Analysis of the Literature): The last phase is separated into a quantitative and qualitative literature analysis. We performed the quantitative analysis with techniques of bibliometric analysis. Beginning with a performance analysis, we analyzed the most important metrics of the research, such as the number of publications per year and citations. These metrics assess the productivity and impact of a research field [18]. Afterward, we conducted science mapping to investigate the relationship between the research articles. We analyzed the author and index keywords using VOSViewer and the co-occurrence [17] feature to derive research streams. The co-occurrence or “co-word analysis assumes that words that frequently appear together have a thematic relationship with one another” [18]. Thus, we obtained different thematic clusters consisting of various keywords using VOSViewer. Compared to a purely manual subjective sorting of research articles, applying a co-word analysis can determine given word correlations exploratively, quantitatively, and objectively [19]. However, as word usage can vary between specific and general [18], we discussed the thematic clusters and their keywords among the authors. We manually refined the topics in these discussions by aggregating and reassigning keywords. Combining both approaches allowed us to minimize their disadvantages. The results of this phase are nine distinguishable thematic clusters representing research streams. Afterward, we continued the analysis using qualitative content analysis [20]. We read every publication and assigned each publication to one stream. Conducting an open coding approach within a group of individual researchers, we marked relevant phrases describing the research objectives and research outlook. By applying the analytical induction [21], we merged similarities to set up topics. For each stream, we could then understand which topics are currently being investigated and which should be investigated in the future.

4 Results

The dataset includes a total of 203 publications spanning 11 active years. These publications involve contributions from 637 authors, demonstrating a diverse and collaborative research environment. Among the publications, 19 were solely authored, while 183 resulted from collaborative efforts. The average productivity per active year of publication is calculated to be 22.44, indicating a consistent output of research within the field. The collaboration index, calculated to be 0.016, suggests a relatively low level of collaboration among authors within the field. However, the collaboration coefficient of 0.68 indicates a moderate degree of collaboration, as most publications result from collaborative efforts. The number of publications steadily increased from one publication in 2015 to two publications in 2016, and further increased in 2017 (4), 2018 (13), 2019 (32), and 2020 (37). In 2021, 61 publications were recorded, followed by 51 publications in 2022. These variations in publication numbers suggest fluctuations in research activity and focus within the field during the examined period. The total number of citations received by the publications amounts to 2757, with an average of 14 citations per publication and 306 per year. Out of the total publications, 137 were cited, representing 67.82% of the overall publications. Results indicate that the publications in this field have acquired significant attention and impact within the scholarly community. Following our research approach, we identified nine different research streams, as shown in Table 1. In the following, the streams are presented. To make our findings more transparent, we exemplary reference selected studies we identified.

The stream of Industry 4.0 addresses a range of research aims to identify, measure, and overcome barriers associated with Industry 4.0 and Internet of Things (IoT) implementation. Publications consider specific industrial environments like manufacturing, farming, food, and electronics. With eight publications, supply chains and their management are one of the key areas of research. Researchers analyze how DT affects procurement processes and their integration into supply chain operations. Research also identifies major barriers hindering the adoption of digital supply chain practices and analyzes their interrelationships. Additionally, the stream concentrates on the readiness and practices of small and medium-sized enterprises (SMEs) in adopting Industry 4.0 either holistically [22,23,24] or with a regional focus [25,26,27,28]. Surveys are conducted to assess the readiness of IoT or Industry 4.0 adoption. Furthermore, the stream includes publications analyzing barriers to DT during the COVID-19 pandemic [29]. Case studies and projects are examined to understand the current status and future prospects of Industry 4.0 implementation. Frameworks and methodologies for DT beyond traditional approaches are proposed to guide companies on their DT journeys.

Regarding further research, the majority of publications do not suggest concrete further research approaches. However, publications state that empirical research and real case scenarios are needed to understand the barriers to the implementation of Industry 4.0, e.g., in sustainability-focused supply chains [30] or manufacturing processes [31]. Research should focus on more sectors beyond just manufacturing [32]. Bertello et al. [33] emphasize the need to monitor SMEs over a longer period of time. In this regard, Ghobakhloo et al. [22] formulate research questions on how SMEs should prioritize approaches to adopting Industry 4.0 technologies and which competence sets SMEs should develop in this context. Furthermore, publications show the need for research to refine maturity models to assess the companies’ status quo and the effectiveness of DT projects. Herceg et al. [32] propose maturity models considering DT holistically by including a broader range of dimensions, such as culture and leadership. With a more holistic perspective in the context of manufacturing, but confirming the previous proposals for future research, some scholars develop research agendas for any dimension of their specifically developed barrier model [8]. These agendas comprise examples of research questions for the barrier dimensions of missing skills, technical barriers, individual barriers, organizational and cultural barriers, and environmental barriers.

The Technology Adoption stream encompasses studies exploring the potential and barriers associated with adopting and implementing new technologies in different industries and organizational contexts like SMEs. The study’s primary objective is to uncover and analyze the factors that hinder or facilitate the integration of these technologies and propose strategies for successful DT. To do so, they are based on literature but also on case studies and surveys. A prominent area of investigation within this stream focuses on the adoption and utilization of blockchain, e.g., in manufacturing [34, 35] and supply chains [36]. These studies aim to identify the potential benefits of blockchain adoption while also analyzing the barriers incumbent companies face in leveraging this technology effectively. Another key aspect of the stream involves studying the impact and operationalizing of artificial intelligence in general [37] or in specific use cases like robotic process automation [38] or container management for smart manufacturing [39].

Table 1. Research streams of barriers to digital transformation.
Full size table

Data-related topics like cybersecurity, big data, and data governance also form important areas of investigation. Studies present conceptual frameworks and propose solutions to enhance organizations’ cybersecurity approaches and data governance systems. In addition, studies aim to understand the requirements and use of big data. In terms of future research directions, the majority of publications do not give a precise research outlook. However, researchers recommend empirical studies that extend the geographical, sectoral, and organizational scope. Furthermore, Flechsig et al. [38] propose to apply quantitative research approaches to validate and complement previous findings. Moreover, Vafadarnikjoo et al. [34] emphasize investigating the interrelationships among identified barriers and other factors.

One major topic in the Service Industry stream is the identification of barriers hindering DT in various service industries [40], such as logistics service providers, cultural heritage management, retail, banking, and legal services. Thus, exploring DT’s drivers [41], as opposed to barriers, influencing digitalization efforts in different sectors, including luxury hotels, sub-Saharan Africa’s financial inclusion, B2B companies, and leading banks, seems a valid research strategy. Other scholars provide insights into successful strategies, leading practices, and organizational elements contributing to effective DT in diverse contexts, such as logistics providers [13], retail operations, and museums’ communication strategies. The investigation of the impact of DT on customer relationships, revenue management, and supply chain risk management. Especially in service industries, innovative digital approaches to navigating external contingencies like the COVID-19 pandemic seem crucial [42]. These approaches might be used in e-Commerce adoption [43] as well as the implementation of banking services.

Based on the studies’ suggestions, future research should explore the role of digital platforms, emerging technologies (e.g., blockchain, AI, IoT), and digital ecosystems in industries like logistics [13], hotels, and banking. Investigating their impact on performance, competitiveness, revenue management, and customer behavior will provide actionable insights. Additionally, developing measurement scales for evaluating the intangible aspects [44] of brand awareness and customer engagement is crucial. Conducting comparative studies across industries and sectors will identify common challenges and opportunities in DT [13]. Examining the influence of different contexts, such as geography, culture, and organizational characteristics, will provide valuable strategies for diverse settings. Larger sample sizes and multi-case, multi-method approaches will enhance generalizability and validity [45]. Research should focus on understanding and addressing barriers to successful DT. Developing adaptable implementation strategies, especially for small organizations [46], will be valuable. Examining the impact of regulations on digital technologies, mobile banking, social media [42], and omnichannel implementation will guide policymakers and organizations.

Studies in the stream of Education include the perspectives of different stakeholder groups, such as students, teachers, and academic and administrative staff, on barriers to DT in education institutions. Schools, as well as public and private universities, are examined. The data are usually based on an individual university or a specific country. Cross-national studies, such as from Eri et al. [47], are rare. In addition, some studies focus on specific subject areas, such as management [48]. The majority of studies present a list or model of identified barriers. The studies are partly influenced by the COVID-19 pandemic or explicitly address the impact of the pandemic [48]. Literature reviews summarize these barriers [49]. Some studies also present recommendations for overcoming barriers [50]. Aditya et al. further aimed at developing a framework for identifying, assessing, and prioritizing barriers, as the “existing literature has reported a barrier list that could affect the implementation of DT in higher education, yet the research question of how to identify barriers remained unanswered” [51].

Regarding research outlooks, many publications recommend an expansion of the database [49]. Studies should aim to validate the results with a more diverse stakeholder group to include different perspectives [48], and explore contextual and sociodemographic factors influencing the perception of barriers [48, 52]. A stronger collaboration among researchers, educators, and industry professionals is emphasized to advance the field [53]. Research is needed to compare barriers in different higher education types [49], to understand how they relate to each other and how they could be overcome [54].

Most papers in the stream Public sector examined barriers to the shift from governments to digital or smart governments [55] or the DT of public administrations [56]. While many studies have addressed barriers to DT within these settings, there have also been studies that have examined the role of governments in causing regulatory barriers [57] or their role in overcoming barriers, e.g., for small service businesses [58]. A few studies deal with the barriers to DT in non-profit organizations [59], also in comparison to for-profit organizations [60]. Ablyazov and Ungvári [61] identified barriers in the smart city context. Compared to the “Healthcare” stream, relatively few papers address specific technologies, such as cloud computing adoption for government services [62].

Future research in this field could include several countries [56] or a large number of organizations in their database “in order to be able to generalize the results” [63]. Quantitative Studies to validate “in various and broader contexts” [64] are advised as with other streams. Studies like these could examine the correlation between the DT process and the barriers [56] or examine the changes over time by performing longitudinal studies [65]. Also, research on a better understanding of the differences between organizational-level and individual-level barriers is recommended [66]. Again, more research on overcoming barriers is called a research outlook [66].

The stream Management focuses on understanding and addressing the opportunities and barriers that organizations and managers encounter when implementing digital technologies. In summary, the publications aim to provide recommendations for action for managing the DT process. The stream emphasizes the importance of managing structural changes and removing organizational barriers influencing the transformation process. The publications address special topics: agile project management [67, 68] and digital entrepreneurship [69]. Except for one publication dealing with the banking sector [70], the stream does not contain sectoral references.

In terms of further research, this stream emphasizes providing insights for managers and organizations navigating the challenges of DT in the future. Studies recommend investigating different industries and organizational processes to improve the understanding of how different methods and actions can be used to overcome barriers to DT. Additionally, Ciampi et al. [67] propose to explore the impact of digital competences on the relationship between DT and organizational agility. Biclesanu et al. [69] suggest cross-country comparisons to broaden the observations and generalize the findings.

Studies in the stream Construction examine the construction industry in different countries such as Germany, South Africa, and North Macedonia. Some focus on the benefits of DT, such as case studies of production robots, 3D printing, and BIM software [71]. Scholars advocate for digital partnering in South Africa’s construction industry based on a survey of construction professionals. The study explores how interactions among architects, clients, contractors, and consultants shape industry characteristics and options for DT [72]. Further studies evaluate BIM adoption, emphasizing barriers in technology and management. Also, opportunities for integrating BIM into education are discussed [73]. Scholars identify barriers to DT in architecture using organizational learning theory. Barriers to DT, such as missing adoption of data-centric approaches or AI-enhanced sensor networks in construction. Finally, scholars research decision-making for end-of-life facilities to promote sustainable practices [74].

Further research should encompass understanding the factors influencing the adoption and successful implementation of digital technologies in construction, such as their drivers, barriers, and enablers. This includes exploring strategies for overcoming resistance to change and identifying best practices for effective adoption [75]. Research should involve developing comprehensive frameworks and methodologies for assessing aspects such as productivity, cost efficiency, sustainability, safety, and quality. At best with quantitative analysis, case studies, and comparative evaluations. Further research on integrating emerging digital technologies, such as artificial intelligence, robotics, augmented reality, and blockchain, is needed to foster innovation in the construction industry [71]. Also, organizational factors such as leadership styles, cultural aspects, change management strategies, collaboration models, and communication approaches need further attention for successful digital partnering and collaboration [73].

Research in the Healthcare stream strongly focuses on technologies, such as monitoring technology [76] or health apps [77]. Poncette et al. [78] examine the barriers to integrating new technologies that are limited to intensive care units. Based on the technology focus of the studies, a large majority of the studies survey the users of the technologies, particularly doctors, nurses, and other clinical staff [79]. Natsiavas et al. [80] examined how citizens feel about sharing their health data with healthcare professionals or eHealth providers. As in other streams, most articles focus on identifying barriers.

In this stream, many studies recommend broadening the data base in future research, e.g., by including more countries to identify cultural differences [79] or more stakeholders, such as patients [79] or the management of healthcare organizations [81]. Further research should also consider environmental characteristics such as the physical environment, the nature of the department, and organizational policies [81]. Several studies also recommend greater validation of results through mixed-method studies [79] or additional quantitative results [81]. The studies in this stream mostly focus on individual areas or technologies, lacking an overall holistic and socio-technical view of an organization. In the “Healthcare” stream, research is needed that applies a comprehensive view of DT as a combination and integration of different digital technologies to improve an organization by triggering significant changes [1].

Residuals cover papers that did not fit into the other streams or covered singular aspects, such as DT in the energy sector, rural areas, or the perceptions and challenges of DT in accounting [82]. Another singular aspect is public sector adaptation to enhance improved service delivery and organizational resilience [83]. Other studies explore barriers to IoT in water management, hinders in small businesses regarding blockchain, or factors stimulating/inhibiting Smart Grid development [84]. Examining cross-cultural barriers in DT highlights technology’’s potential in diverse business environments. More generally, some papers examine barriers and enablers of DT. One proposes a socio-technical model categorizing barriers [85].

Future work is suggested by further analyzing living labs and rural stakeholders’ context to identify driver barriers and impact patterns. Co-designing a system and developing requirements for citizen involvement is necessary [83]. In accounting, research should focus on the impact of digitalization and the role of public entities [82]. Investigating resistance to change, culture, and price as barriers is crucial. For digitalization in the energy sector, research should explore managerial barriers and evaluate opportunities, risks, and competencies [84]. Especially for generic models, larger samples and in-depth analysis are needed. Research involves collecting quantitative data, using mixed-methods approaches, and adapting models as digitalization evolves [85].

5 Concluding Discussion

This mapping study has provided a comprehensive analysis of the research streams. The identified streams offer a holistic understanding of the multifaceted nature of this research field and provide a foundation for future studies in this field. Our findings indicate a strong thematic focus on private-sector companies. The underlying reasons for this can be multifaceted. Due to the strong economic importance or their impact on society, this sector might be in the spotlight. Industry frequently serves as a leading example, e.g., achieving efficiency gains, adapting to evolving work dynamics, and exploring diverse avenues for value creation [86]. The unequal distribution could be related to DT’s advancement, data availability, research funding, or research interests. This has different implications for research in the field of DT barriers. Looking at the different streams in comparison helps identify gaps in less advanced streams. In addition, the degree to which findings can be transferred should be examined. Collaboration among researchers from different disciplines and industries could provide new insights.

Although the streams differ regarding their themes, certain commonalities can be observed regarding the research approaches in the studies. It is striking that most of the studies adopt a qualitative approach. Quantitative and mixed-method approaches, by contrast, are much rarer. The high proportion of qualitative studies could be related to the relatively young age of the research field and the short publication period of most studies starting from 2019. For a research field with little pre-existing knowledge, qualitative research is better suited to gain new insights compared to quantitative approaches [87]. In the light of model development phases [88], most publications are in the phase of designing the models, respectively identifying the barriers. Research must now address “how this can be measured” [89]. Then, scholars need to test and evaluate the models to assess their reliability, validity, and generalizability [88, 89]. Measurement instruments and procedural models can also help practitioners to identify and prioritize barriers in specific real-world scenarios [51]. Research also needs to develop recommendations for overcoming barriers effectively. Barriers could become facilitators if they are mastered [9]. A wider use of quantitative approaches would also allow the examination of the relationship between barriers and other constructs, such as the DT process or financial metrics. In addition, which factors have an influence on the perception of barriers could be investigated. Noticeable, however, is a lack of a clear research outlook in many scientific articles. A clear research outlook is essential for guiding future research efforts and identifying emerging trends and challenges within the field. Researchers should strive to provide a concise but explicit research outlook in their articles, highlighting the areas for further investigation.

The implications of our study are manifold. Our study provides an overview of the research efforts in the field and guides scientists in their future research. The study also offers implications for practitioners who want to embrace DT. It allows them to get a quick and systematic overview of the current body of knowledge and evidence in the field of barriers to DT. The streams related to industries especially allow practitioners to better identify barriers and help accelerate the DT process, e.g., how to develop and implement strategies or what corporate culture and competencies are advantageous. Further, for academics, the more general streams can serve as a broader perspective in driving research programs forward. Also, our work identifies underrepresented streams and topics of future interest, serving as a foundation for formulating funding programs.

However, it is essential to acknowledge the limitations of this study. As the research field continually evolves, stream changes will likely occur over time. By combining a bibliometric with a systematic literature review, we attempted to counterbalance the disadvantages of each method to derive the streams objectively. However, it is still possible that other scientists will reach a different outcome through different inferences or methods. Further, the restriction to the Scopus database and the inclusion and exclusion criteria used to select relevant literature may have influenced the results.

Our mapping study has already revealed several research needs, which are presented in the result section. Regarding research on the streams in barriers to DT, we can further note that future research should focus on exploring specific research streams in greater detail to provide more nuanced insights. Periodic reviews should be conducted to determine how the research field is changing. Further research could also include perspectives from practitioners and industry to derive a more comprehensive research agenda.