Workplace literacy skills—how information and digital literacy affect adoption of digital technology

Shahrokh Nikou (Department of Information Studies, Faculty of Social Sciences, Business, and Economics, Åbo Akademi, Åbo, Finland) (Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden)
Mark De Reuver (Delft University of Technology, Delft, The Netherlands)
Matin Mahboob Kanafi (INERACT Unit, University of Oulu, Oulu, Finland)

Journal of Documentation

ISSN: 0022-0418

Article publication date: 3 May 2022

740

Abstract

Purpose

Information and digital literacy have recently received much interest, and they are being viewed as critical strategic organisational resources and skills that employees need to obtain in order to function at their workplaces. Yet, the role of employees' literacy seems to be neglected in current literature. This paper aims to explore the roles that information and digital literacy play on the employees' perception in relation to usefulness and ease of use of digital technologies and consequently their intention to use technology in the practices they perform at the workplace.

Design/methodology/approach

This paper builds a conceptual model with key constructs (information literacy and digital literacy) as new antecedents to the technology acceptance model and aims to establish that information literacy and digital literacy are indirect determinants of employees' intention to use digital technologies at the workplace. The data set used in this paper comprises of 121 respondents and structural equation modelling was used.

Findings

The findings reveal that both information literacy and digital literacy have a direct impact on perceived ease of use of technology but not on the perceive usefulness. The findings also show that both literacies have an indirect impact on the intention to use digital technology at work via attitude towards use.

Practical implications

Managers and decision-makers should pay close attention to the literacy levels of their staff. Because literacies are such an important skillset in the digital age, managers and chief information officers may want to start by identifying which work groups or individuals require literacy training and instruction, and then provide specific and relevant training or literacy interventions to help those who lack sufficient literacy.

Originality/value

This is one of the first studies to consider information literacy and digital literacy as new antecedents of the technology acceptance model at the workplace environment.

Keywords

Citation

Nikou, S., De Reuver, M. and Mahboob Kanafi, M. (2022), "Workplace literacy skills—how information and digital literacy affect adoption of digital technology", Journal of Documentation, Vol. 78 No. 7, pp. 371-391. https://doi.org/10.1108/JD-12-2021-0241

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Shahrokh Nikou, Mark De Reuver and Matin Mahboob Kanafi

License

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


Introduction

Digitalisation is radically transforming job design, job resources, professional and economic activities all over the world, which warrant continuous exploration of how workplace digitalisation influences employees' engagement (Chan et al., 2021). Digitalisation is the application of digital technologies and infrastructures in business, economy and society (Autio, 2017). Unexpected incidents could also make the digitalisation process even more complex and add new challenges to digital transformation journey (Iivari et al., 2020; König et al., 2020). For example, recent global pandemic situation has added a fair amount of complexity in, e.g. skills needed to execute remote work, activities and operations of the organisations. This is especially a major challenge for organisations which are used to traditional ways of performing their daily and routine activities. To cope with the challenges imposed by the digitalisation, organisations need to develop digital strategies and strive to identify the key success factors for their digital transformation journey (Hess et al., 2016; Vial, 2019). Organisations that are unable to meet the timely and harmonised adoption, implementation and use of technological solutions will, inevitably, fail to flourish or in the worst case to survive. In addition, the real challenge of digitalisation is not merely technology, as introducing new technology into the workplace is not about hardware or software, it is about workforce who need to adopt to change, know how to use technology and their post-adoptive behaviours (Bala and Venkatesh, 2016; Colbert et al., 2016). In this regard, Farrell et al. (2021) recently discovered that there is widespread agreement amongst policymakers that the existing workforce's literacies are inadequate to meet the literacy demands of the future workplace.

Therefore, organisations not only must adopt strategies to deal with digitalisation but also need to have a coherent strategy that includes a plan to reskill their workforces (Berger and Frey, 2016; Kane et al., 2019). Moreover, in today's complex information landscape, the concept of literacy goes beyond being able to read and write that an individual either has or is lacking (Bawden, 2001). Literacy is considered as a range of competences [1], knowledge, and skills needed by people in different situations of their lives and through relationships with the colleagues, the communities and the environments in which they interact (Panel, 2002). As such, employers are looking more and more to hire new workforces with a high degree of literacies such as information literacy (IL) and digital literacy (DL) (e.g. Mietzner and Kamprath, 2013) and media literacy (Collard et al., 2017). Such literacies have been identified as essential and generic skills as well as personal attributes in the digital age (Bowen and Johnson, 2019; Farrell et al., 2021; Foster, 2019; Dede, 2010). Thus, it can be argued that to deliver an efficient transformative digitalisation and to become a digital prepared workplace, workplace literacies are necessary for all types of organisations, jobs titles, job design and individuals to enhance and fulfil their task performance, or even be evaluated as a productive employee.

We acknowledge that the terms literacies and skill-based literacies (Bawden, 2001; Stordy, 2015), are more suited to complex information settings, incorporating different types of literacy (e.g. information, digital, media, library and computer). However, in this paper, we will focus on IL and DL as they are primary and essential literacies, which have taken a centre stage in debates of individuals' abilities to access, retrieve and critically analyse the information that flows through digital technology in workplace context. In today's information-based digital era, knowing about information processing and technology enhances not only individual performance, but also organisational performance. In addition, we are aware that there are several definitions of IL and DL in the literature (e.g. Bawden, 2001; Lloyd, 2012; Stordy, 2015), and there are no agreed upon definitions for IL and DL. In this paper, we use the American Library Association definitions of IL and DL, which has produced often-quoted definitions.

IL is defined as a set of abilities to recognise when information is needed, to initiate search strategies to locate, evaluate, assess, analyse and effectively use the needed information, and to make decisions in formal and informal learning contexts, at work, at home and at the educational settings (ACRL, 2017, p. 12; Serap Kurbanoglu et al., 2006). DL is defined as the ability to use information and communication technologies to find, evaluate, create and communicate information, requiring both cognitive and technical skills (American Library Association, 2012, p. 1). So, while IL deals with information processing, DL is the awareness, attitude and ability of individuals to appropriately use and interact with digital technology (tools) to easily and effectively access information in different formats (e.g. text, videos and images) in a digital environment (Cetindamar et al., 2021; Stordy, 2015; Van Dijk and Van Deursen, 2014).

The need for IL and DL has been highlighted in the literature as a critical dynamic capability of organisations during their digital transformations (Cetindamar et al., 2021), and both literacies are considered as skills based on knowledge, perceptions and attitudes (Bawden, 2001). For example, Gui and Argentin (2011), have emphasised the need for and the relevance of both IL and DL in various workplace settings. Middleton et al. (2018), and Somerville et al. (2017), highlighted the critical role of literacies to perform tasks to achieve goals, success at workplaces and work performance in general. Moreover, employers are increasingly requiring their employees to acquire and develop critical literacies prior to starting work, as they are needed to meet organisational objectives (Kane et al., 2019), and to cope with increasingly complex information environment at workplace (Raish and Rim-land, 2016; Van Laar et al., 2017, p. 577). Therefore, workforce in digital age not only needs technological skills, but also the ability to adapt to changing and evolving job requirements (Ahmad et al., 2013; Carnevale and Smith, 2013). Such workforces are expected to equip with skills, knowledge and abilities that fill the gap between existing and needed digital competencies (Ancarani and Di Mauro, 2018; Cetindamar et al., 2021; Murawski and Bick, 2017).

From a theoretical perspective, while research on IL and DL mostly focuses on the educational contexts (e.g. Jang et al., 2021; Mohammadyari and Singh, 2015; Ng, 2012), at the workplace context there are limited contributions where IL and DL are conceptualised and integrated into traditional models such as technology acceptance model (TAM: Davic, 1989). We also recognise that there is a wealth of research on intention to use technology and acknowledge that there are a large number of important contributions helping to understand what drives intention to use technology. However, given the importance of literacies at workplace, this paper aims to examine how IL and DL would impact employees' intention to use digital technology. In other words, it is not the aim of this paper to explain adoption/acceptance better, as the usage of these digital technologies in the workplace is now a common thing. Instead, the aim is to understand how IL and DL can be conceptualised at workplace context and how they influence the use of technology at the workplace. The next theoretical advance is to understand the explanatory power (if any) of these literacies on well-established theoretical models on the usage of digital technologies. In this way, our contribution is towards the literacy theory, examining the explanatory power of the IL and DL as a separate construct in a theoretical domain of technology acceptance.

Therefore, we include IL and DL as new antecedents of the TAM model (Davis, 1989). We argue that both IL and DL directly influence the TAM determinants, (perceived usefulness: PU, perceived ease of use: PEoU, and attitude towards use: ATU). Thus, IL and DL indirectly affect the intention to use technology at workplace mediated through the ATU. However, we are aware that the impact of literacies may depend on the type of technology (e.g. newness). If an employee knows well about the information environment (IL) and is able to use technology to retrieve and access information (DL), they may have a better understanding of technology, and find it easier to use (PEoU), therefore appreciating the usefulness (PU).

This paper contributes to both literacy and technology acceptance literature by providing a grounded understanding of the relationship between IL, DL, ATU and intention to use digital technology at workplace. The question directing this research is “what role does information and digital literacy play in the intention of employees to use digital technology at workplace?” To answer the question, we conducted empirical research, and collected data from respondents working in different workplaces in Finland. The data were analysed using partial least square structural equation modelling (PLS-SEM) technique. This paper expects to contribute to literature, by fostering the understanding of and adding essential knowledge about conceptualisation of IL and DL at workplace context. The remainder of the paper is laid out as follows. The following section will provide background information, followed by a theoretical discussion and the development of hypotheses. Then, we provide the research methodology and discussion of the results and the major findings. Finally, discussion and conclusion are presented followed by discussion on future work suggestions and limitations.

Literature review

In workplaces, information and knowledge are seen as providing a competitive advantage in business and in service provision. Therefore, information literate employees who can locate, evaluate and effectively use information) are an increasingly important strategic resource for organisations (Kirton and Barham, 2005; Lloyd, 2003; Middleton and Hall, 2021; Oman, 2001). Moreover, as information technology has become more flawless and user-friendly (Bilgihan, 2016), it is increasingly important to consider how individuals can interact with and apply the information at workplace context, which advanced technology makes accessible. In a workplace context, where individuals, specifically older generations of workforces, continue to resist adopting information technology (Lapointe and Rivard, 2005), the constant demand for decision-making and problem-solving abilities demonstrates the necessity for a highly skilled, competent and adaptive workforces (Simao and Franco, 2018; Renta-Davids et al., 2014). Such abilities are needed next to the ability to interact with technology and information effectively (Urena et al., 2019). In addition, with the rapidly changing landscape of digital technology at workplaces and demands of local, state, national and global economies (Nafukho et al., 2017), employees are expected to be not only information literate, but also be equipped with other types of literacies, such as ICT literacy, technology literacy, media literacy, net/online literacy (Kasemsap, 2018; Marsh, 2018). These broad arrays of literacies enable workers to interact with technology and understand what the technology is and how to use it (Cetindamar et al., 2021).

The importance of DL cannot be neglected, given today's modern workplaces. Eshet (2004, p. 100), argued that “to succeed in today's working environment, individuals must be able to use a diverse range of technologies”. The author asserted that “DL includes a large variety of complex cognitive, motor, sociological, and emotional skills, which users need to function effectively in digital environments” (p. 93). Hunter (2018) also argued that in the digital era and in the workplace context, DL goes beyond functional IT skills and includes a richer set of digital behaviours, practices and identities, and that DL involves more than the mere ability to use software or operate a digital device. Furthermore, Ng (2012), introduced a framework of DL to investigate the ease of using unfamiliar digital technology amongst students in the educational context. The author found that for digital native (debatable concept) students, the technical aspects of unfamiliar technologies were not of foremost concern and concluded that if individuals are given the opportunity to engage with a purpose for adopting digital tools, they will be able to use and apply them in more appropriate and meaningful ways (Ng, 2012, p. 1077).

The workplace poses a specific context that affects the role of IL and DL, compared to; for instance, the educational context. Some studies (e.g. Colbert et al., 2016) have shown that, in the digital era, different views exist on how employees perceive the impact of technology in their day-to-day activities. For example, Kohnke (2017) stated factors that influence the new generation of workforces' intention to use digital technologies might be different from others at workplaces. The individuals with low literacies are less likely to be critical about the usefulness of technology or may find it difficult to use the work-related technology. Whereas those with higher literacies may be more confident to adopt the technology and establish a positive attitude towards the use of technology (Cetindamar et al., 2021). Mohammadyari and Singh (2015), asserted that individuals with higher literacies would find the cognitive challenges of using different technology less difficult because they may be familiar with the content, interfaces, access choices, terminology and norms of new tools, amongst other things. Forster (2017) also argued that the new generation of workforces uses a wider range of new approaches to deal with information at the workplace and evaluate their interactions with information differently in terms of meaning, value, practices, and purpose. According to Forester (2017), at the workplace context, failure to access and use the most up-to-date and relevant information is not only a professional but also an ethical failure. At the workplace, IL, which is facilitated by a variety of business applications and ICT technologies, is a means to an end, and employees must interact with information both individually and with others to create business values. In contrast, in the educational setting, higher literacies help students to better understand the process of finding, analysing, summarising, integrating and presenting information for the learning and research objectives (Cheuk, 2017). In the workplace context, literacies are central to both personal and organisational performance and success, and are more context-specific, founded in practice rather than norms and generic guidelines, less structured and more collaborative than in higher education (Goldstein and Whitworth, 2015, p. 71).

Theoretical model and hypothesis development

To assess and evaluate the antecedent of intention to use technology at workplace, we draw on conventional acceptance theory (i.e. TAM) and integrated both IL and DL as new antecedents into the research model. In the following sub-sections, we motivate and justify our choice of theory and postulate several hypotheses depicting the path relationships in the research model (Figure 1).

Information literacy and digital literacy

Yu et al. (2017, p. 198) argued that IL enables people to master information content and extend their investigations to recognise when information is needed, and to effectively locate, evaluate and use the needed information. Ng (2012) argued that an information literate person is a critical thinker who can locate, and productively evaluate web-based information. Both Yu et al. (2017), and Ng (2012), studies are in line with the definition of IL provided by ACRL (2017, p. 12), where both studies refer to individual's abilities and skills required to operate in our contemporary complex information environment. In addition, the requirements for becoming an information literate may not be common in all contexts, but the ability of the workforce to effectively use information, locate, evaluate, store, retrieve and communicate is vital to the success of any organisation (Kirton and Barham, 2005). In the workplace context, one of the main causes for the workforce's low level of IL is a lack of effective IL training preparation (Gilbert, 2017; Kirton and Barham, 2005). Naveed and Rafique (2018), for example, investigated the scientists' IL and discovered that while they were confident and knowledgeable in using searching tools and electronic information services, they were less confident in understanding and evaluating the quality of the information they collected. The authors concluded that workplaces must have standardised IL preparation and instruction programmes for their employees to improve their IL. In addition, Chang et al. (2020, p. 7) studied the impact of IL of nursing workforce and found that IL had a positive effect on their attitude, performance and effort expectancies, and thereby enhances the nursing information systems usage intentions.

While IL is an overarching concept for describing a persons' ability to manage and use information for different purposes, DL focusses the interaction with technology and the use ICTs to search, find and the use of information. For example, Gilbert (2017) not only found that organisations require generally diverse types of IL, which are the ability to use various resources and tools, to synthesise information, to evaluate information, to use information in practice, and to collaborate with colleagues, but also discovered that digital skills are highly expected from the workforces in the virtual world.

From a theoretical standpoint, Durodolu (2016), adopted the TAM model and found that the employees' resistance to information systems is the main factor for the failure of adoption of new technology in attaining IL. Moreover, Yoon (2016), found that both construct of TAM (i.e. PU and PEoU) had significant impact on the user's attitude and their intention to use mobile library applications. Booker et al. (2012), also used the TAM model and found that the amount of IL instruction and education considerably influence business students' attitude towards and intention to adopt online library resources. In addition, Oluwajana and Adeshola (2021), used the unified theory of acceptance and use of technology (UTAUT) model in higher education context, and found that students' perceptions of DL had a positive and significant impact on their attitude and behavioural intention to utilise digital learning tools. In addition, Nikou et al. (2019), and Nikou and Aavakare (2021), also in the educational context, investigated how DL impacts individual's intention to use digital technology and found that DL positively impacts the intention to use digital technologies for learning and teaching. Mohammadyari and Singh (2015), investigated the impact of DL on the employees' intention to use technology in small and medium-sized enterprises (SMEs) context and found that DL significantly impact the users' performance and intentions to use Web 2.0 tools.

Moreover, according to Ng (2012), a digitally literate individual possesses the technical and operational skills to use technology for various reasons, since DL is a system of skills and strategies employed by learners and users in digital settings. The author stated that DL is an intersection between three dimensions of technical, cognitive and social-emotional (Ng, 2012). In terms of technical dimension, employees are expected to be knowledgeable with the use of ICTs and have the ability to properly operate digital technologies such as the internet, computers, company's internal Web portals (intranet) and platforms in their workplace. Cognitive dimension refers to the ability to operate digital technology critically, being able to evaluate and properly manage digital information. Ng (2012) and some other authors stated that such ability significantly increases network navigation and help to avoid disorientation issues, and improve the knowledge building ability (Eshet, 2004, p. 100; Lee and Hsu, 2002). Therefore, such competence necessitates an employee's knowledge of ethical and moral issue problems, as well as the ability to assess the validity of resources (e.g. copyrights and plagiarism) (Ng, 2012, p. 1068). Finally, the social-emotional dimension involves being able to use Internet responsibly for communicating, socialising and learning, respecting others' privacy and adhering to ethical rules in different contexts and environments (Ng, 2012, p. 1068).

All in all, in the workplace context, we argue that both IL and DL affect workforce's perception of ease of use and but not the perception of usefulness of the technology. This is mainly due to the assumption that higher literacies may make people more critical, and hence less convinced. However, this depends on the type of technology and the quality. For instance, a badly designed technology may receive critical reception from individuals with higher literacies, whereas a well-designed one may be appreciated by individuals with higher literacies. In other words, an individual with high level of literacy is confident enough that she or he can use newly introduced technology at workplace but might be sceptical about it usefulness unless using the technology in practice, hence:

H1a.

IL has a positive effect on ease of use of the technology at workplace

H1b.

IL has no effect on the usefulness of the technology at workplace

H2a.

DL has a positive effect on ease of use of the technology at workplace

H2b.

DL has no effect on the usefulness of the technology at workplace

Perceived usefulness and perceived ease of use

TAM (Davis, 1989) is an established and widely used theoretical model in research on acceptance and adoption of new technological solutions both at the individual and organisational level. The determinants in the model are PU (subjective perception of users where they believe that using certain technologies can improve the performance of their work), PEoU (subjective perception of users who believe that using a particular system will be free from effort) and ATU (Davis, 1989). In this research, we focus on these main determinants of technology acceptance, while we could use and employ other adaptation or extended model of TAM such as UTAUT and UTAUT II (Venkatesh et al., 2003, 2012). The main reason of such conceptualisation is the core theoretical aim of this research, which is adding IL and DL into an established theoretical model, and assessing the role that these literacies, through the TAM determinants, play on the intention to use technology at workplace. Prior studies showed that PEoU has a significant effect on the PU (Sun et al., 2009), and that both PU and PEoU have a positive impact on the ATU of technology (Fagan et al., 2008). Although the core relations in the TAM model are well-tested, we include them here as hypotheses as we aim to examine whether IL and DL indirectly affect attitude, mediated through PU or PEoU. Murray (2011), in a study of cross-generational workforce stated that it comes as no surprise that different generations respond to and utilise emerging technology in different ways. According to the author, as more millennials take on leadership roles, their ATU of technology will lead to different leadership standards than their predecessor generation, hence:

H3.

PU has a significant effect on ATU of technology

H4.

PEoU has a significant effect on ATU of technology

H4a.

PEoU has a significant effect on PU

Attitude towards use

In a study of employees' ATU of technology in hospitability context, Solnet et al. (2012), found that individuals born between 1979 and 1994, exhibit different attitude to previous generations of employees entering the workforce and found that they embrace technology differently and takes electronic collaboration for granted (Solnet et al., 2012). Moreover, Cai et al. (2017) in their meta-analysis on ATU of technology found that men exhibit more favourable attitude towards technology use than women and found that the attitudinal differences towards technology use are often based on the individual characteristics such as age, gender and educational status, but the level of technology competency has often higher impact on the ATU of technology (p. 10). Oh et al. (2019) studied employees' attitude towards use of smart factory technology (e.g. big data technology, automation technology and supply chain integration technology) and found that employees with more favourable attitude towards technology tend to be more positive to experience and use new technology. The authors concluded that the success of a business heavily depends on organisation and individual related factors such as employees' ATU of technology and perceived ease of technology use (Oh et al., 2019, p. 13).

Moreover, Ng (2012), studied students' attitude towards using e-learning technology in their learning before and after a course and did not find significant differences in the students' attitude; however, it was found that students were more positive towards using the technology in the learning after the course ended. Finally, Kimiloglu et al. (2017), used a sample of 106 of the top 500 corporations in Turkey and studied the ATU of e-learning technology for corporate training and found that most companies had a positive ATU of e-learning technology as they perceive advantages by infusing it into their established practices (Kimiloglu et al., 2017, p. 347), hence:

H5.

ATU has a positive effect on the intention to use technology at workplace

Intention to use technology at workplace

In this paper, intention to use technology at workplace is the dependent variable. Gu et al. (2013), conducted research on the antecedents that influence technology acceptance and discovered that the difference in technology adoption is dependent on how people use technology and how essential they find it to be. Moreover, Behringer and Sassenberg (2015), surveyed 315 employees within an organisation to determine if they intent to adopt new and emerging technologies at their workplace. The findings showed that positive intention could have an impact on employees' future usage of technology for exchanging knowledge within the organisation. Thus, the research model uses intention to use technology at the workplace as a dependent variable, see Figure 1.

Research methodology

We did not restrict the data collection on any particular sector, workplace domain, or company since this was an exploratory study. An online survey questionnaire was created to collect data before distributing the final version of the survey; we conducted a pilot study with 15 experts (industry and academic experts) to get their feedback on the clarity of the questions in the survey. We used a list of businesses and companies where Finnish workforces are registered in designated platforms to collect data and invitations were sent to potential respondents using that list. We also requested some employees' associations in Finland to share and post a link to the survey on their social media pages. The participants were then asked a series of questions about their personal characteristics (age, gender, education and type of organisation or industry sector).

Measures and survey instruments

Theoretical constructs were operationalised using validated items from prior research (see Appendix), some minor adjustments were made to better adapt to the context of this research. PU (five items) and PEoU (six items) were derived from Davis (1989). For measuring ATU of digital technology at workplace, five items were derived from Ng (2012). For example, “I like using digital technologies for working and learning”, “I work/learn better with digital technologies”. For measuring intention to use technology, we used seven items derived from Lin and Lu (2011), and Venkatesh et al. (2003). For example, we asked questions such as “I would expect to use digital technologies to seek for information”, or “I will continue using digital technologies in the future”. The literacies scales, DL with ten items and IL with seven items were derived from (Ng, 2012; Serap Kurbanoglu et al., 2006). For DL, we asked, e.g. “I know how to solve my own technical (ICT related) problems”, or “I know about a lot of different digital technologies” or “digital technology enables me to collaborate better with my colleagues on project work and other working/learning activities”. For IL, we asked “I am sometimes unsure of how much information I need for solving work related problems” or “I can determine the authoritativeness, correctness and reliability of the information”. All items were measured on a 7-point Likert scale, where “1 = strongly disagree” to “7 = strongly agree” and SEM using SmartPLS was used to analysis the data.

Data collection and descriptive statistics

In the course of four weeks, a total of 210 survey invitations were sent, and 121 complete questionnaires were returned. As suggested by Hair et al. (2011), we performed the non-response bias test, comparing the first 25% of respondents with the final 25% of respondents for all survey items using the chi-square test. The non-response bias test result showed that the respondents do not differ significantly, thus we concluded that data are not biased.

Of the respondents participating in this research 61% (n = 74) were men and 37% (n = 45) were women, two respondents did not indicate their gender. The average age of the respondents was 36.7 years old with a minimum being 21 and a maximum being 64 years old. Most of the respondents had either a bachelor's degree or a master's degree (see Table 1). When we asked respondents to choose a category that best describes the industry they work for, 20% mentioned they work in the educational institutions, 15% mentioned they work for the scientific and technical service organisations and 11% mentioned they work for a software company. The rest indicated working for, finance and insurance, retail, construction, mining, information services and data processing. Moreover, 80 (66%) respondents indicated that they work for the private sectors, 30 respondents worked for the public sectors and only five respondents indicated they work for non-profit organisations, see Table 1.

We also asked respondents to rate “1: Not proficient at all, 4: Neutral and 7: Very proficient”, their proficiency with using digital devices, software and applications. Table 2 shows that respondents have scored above the average in all items. For instance, over 74.4% of them mentioned they were proficient or very proficient with MS Office, and as much as 61% mentioned they were proficient or very proficient with file sharing applications (e.g. Dropbox).

Data analysis and measurement model results

Gefen and Straub (2005) recommended analysing the path relationships in the research model following first the measurement model and then the structural model. All indicators (survey items) were reflective in our model; therefore, we assessed the reliability and validity of the items (Hair et al., 2013), by examining the outer loadings, composite reliability and average variance extracted (AVE) analysis. As indicated by Hulland (1999) the values of outer loadings should be above 0.70, in this paper all indicators were loaded on their respective constructs with primary loadings of 0.70 or above (see Table 3). However, items IL2, DL10 and INT7, from IL, DL and intention to use were removed due to low factor loading threshold. But it should be noted that this does not create any validity issues, as we have enough number of items in those constructs. Moreover, the items are reflective, meaning that one item can be replaced for another without affecting the meaning of the scale. The low value of factor loading indicates that the item did not measure its respective construct.

Moreover, composite reliability (CR) test examining the internal consistency was computed and all values were all above the threshold of 0.70 (Hair et al., 2011) or higher with the minimum of 0.878. Also, we performed convergent validity test by computing the AVE values for each contruct. The results showed that all values were above the recommended value of 0.50 (Bagozzi and Yi, 1988), with the minimum value of 0.591 for IL.

To examine the internal consistency of latent constructs, Cronbach's alpha values were assessed, and the results showed that all constructs had higher value above the recommended threshold of 0.70. Nevertheless, as indicated by some authors (e.g. Bagozzi and Yi, 1988; Hair et al., 2012), Cronbach's alpha (α) tends to provide a conservative measurement in PLS-SEM and it is often used to measure internal consistency reliability; therefore, it is recommended to use the CR as a replacement (Hair et al., 2012), see Table 3.

We also checked the common method bias (CMB), to see if any bias attributed to the measurement method could be found by following two different approaches. In the first approach, we computed Harman's one-factor test, as recommended by Podsakoff et al. (2003). The test result showed that none of the constructs had a value of more than 50% of the variance. In the second approach, the CMB was assessed via the common latent factor (CLF) technique. Podsakoff et al. (2012) argued that the CLF provides a more robust understanding of the CMB than from Harman's one-factor test. So, we compared the chi-square values of two models: unconstrained model and a model where all the paths were constrained to zero. The result showed that no path in the model was affected by CMB.

Finally, the discriminant validity test was computed to assess for the uniqueness of a measuring construct, using the value of the square root of AVE in each latent variable Henseler et al. (2015). The results indicated that data are free from discriminant validity issue (Fornell and Larcker 1981) and provided evidence suggesting reasonable discriminant validity in the data, see Table 4.

We assessed the discriminant validity using the heterotrait-monotrait (HTMT) ratio of correlations to establish that a reflective construct has the strongest relationships with its own indicators. The results of HTMT showed no issue that our data suffers from discriminant validity, see Table 5.

Structural model results

To test the research hypotheses and examine the path relationships between constructs in the model, SEM technique was employed. The SEM results showed that the intention to use digital technology at workplace was explained by variance of 21% and attitude towards use (ATU) was explained by variance of 52%. The SEM results showed that both IL (β = 0.36, t = 4.297, p < 0.001) and DL (β = 0.55, t = 6.447, p < 0.001) had a significant effect on the PEoU; therefore, both H1a and H2a were supported by the model (Figure 2).

As expected, the SEM results show that neither IL nor DL has any significant effect on PU; therefore, both H1b and H2b were supported by the model. In addition, the SEM results reveal that both PU (β = 0.37, t = 4.427, p < 0.001) and PEoU (β = 0.39, t = 5.483, p < 0.001) significantly influence ATU; therefore, both H3 and H4 were supported by the model. In addition, the path between PEoU and PU (β = 0.33, t = 2.058, p < 0.05) was found to be significant; therefore, H4a was supported by the model. Finally, the path relationship between ATU and intention to use technology at workplace was found to be significant (β = 0.40, t = 5.136, p < 0.001); thus, H5 was supported as well.

We also tested the mediation result, accounting for the role ATU play between IL and DL to intention to use technology at workplace. The results showed that there are indirect effect of IL and DL to intention to use, mediated through ATU, such that IL (β = 0.08, t = 2.525, p < 0.01), and DL (β = 0.11, t = 2.819, p < 0.05), both indirectly influence the participants' intention to use technology at workplace. It should be noted that both effects are through PEoU, and we did not find any mediation effect through the PU.

Discussion

According to Prensky (2001a, b), one of the main reasons for the disparity in perceptions of technology's impact is that many employees come from a generation that is essentially resistant to change. As such, this may cause a divide between workforces who embrace digital technologies and those who do not, necessitating the need to study IL and DL in relation to technology acceptance. However, we acknowledge that there is fairly strong (Kirschner and De Bruyckere, 2017) and seems to be widespread debate about the Prensky's classification of individuals based on their age as digital natives and digital immigrants (Vodanovich et al., 2010; Wang et al., 2012), suggesting that the terms need to be refined further through more extensive research on individual's interactions with information, and digital technology. Therefore, in this paper, we developed a conceptual model, integrating IL and DL as antecedents of TAM model to examine the intention to use technology at the workplace. The SEM results reveal that both dimensions of modern literacies, i.e. IL and DL significantly, but indirectly, impact the intention to use technology at workplace context.

We also found that while IL and DL both positively influence the perception of ease of use (PEoU) technology, they do not have any impact of the employees' PU of technology. A plausible reason for such results could be as if an individual knows better how to use technology, or how to process digital information, then it seems easier to her or him to use the digital technologies at workplace. Whereas the technology does not become directly more useful if she or he knows how to use technologies. To put it another way, we argue that individual with higher level IL and DL are more comfortable to use digital technology to retrieve information from information sources. A potential explanation is that people that understand how to retrieve information from (digital) technologies find it easier to use these technologies. Possibly, highly literate workers are more comfortable dealing with technologies, making them more positive about the expected ease of use. Arguably, the impact could differ between technologies: well (or poorly) designed technologies may in fact be recognised to be so by highly literate workers, and thus be evaluated more positively (or negatively) on ease of use. In our study, we focussed on well-known and established workplace technologies, and it would be interesting to replicate our findings for novel technologies that have not yet found their dominant design.

Another interesting finding is that, in line with our expectation, literacies have no influence on the PU of digital technologies in the workplace environment. Apparently, workers do not evaluate the utility of technologies, for instance for achieving their tasks, in light of their literacy skills. This interpretation lends support to a core idea in the TAM model, which is that ease of use and usefulness are separate concepts, and that ease of use is a necessary yet not sufficient condition for usefulness. Alternatively, the literacy skills play no role in the assessment of utility of a technology. This would imply that workers need no literacies in order to appreciate (or disapprove of) the usefulness of a technology to achieve their goals. Once more, a caveat is the type of technology being discussed: for well-designed and appropriate digital technologies, workers with high literacies may be more appreciative of the usefulness, while the same highly literate workers may be more capable of seeing through less appropriate technologies.

The findings also revealed that both IL and DL influence the development of a positive attitude towards the usage of technology at work via PU and PEoU. This is an interesting result, as we found a significant positive relationship between attitude towards technology use (β = 0.40, t = 5.136, p 0.001), and intention to use technology at workplace.

These findings point to the relevance of workplace literacy and show that employees' IL and DL may have direct impact on their personal achievement and organisation performance. As a result, a greater understanding of technology acceptance in the workplace may aid in better predicting the use of new information resources. In addition, our findings regarding the impact of IL to workforce's intention to use technology supports earlier findings of Durodolu (2016), who also indicated that IL has a significant effect on adoption of new technology. The results obtained in this paper are also in line with Yu et al. (2017), who also found that both IL and digital skills impact adoption behaviour and concluded that the level of IL of the individuals is an important factor. The results also showed that our proposed conceptual model is an appropriate model for literacy research at workplace context, and differs to some extent, to educational models, as the effect of both IL and DL in workplace is central to both professional and organisational performance. Our findings are similar to Forester's (2017), who argued that at workplace context, ability to access and use of relevant information is directly associated with the professional and also organisational achievement.

Conclusion

This is one of the first studies which includes IL and DL as new antecedents of TAM in the workplace context measuring the workforce intention to use digital technology. Building on the IL and DL, we theoretically contribute to the acceptance literature by showing that these two dimensions of literacy in modern workplace impact workforces' decisions to use digital technology at their workplaces. Given that the inclusion of IL and DL, in addition to PU and PEoU explained as much as 52% of the variance in the ATU of technology, we argue that we may be approaching the possibility to explain individuals' decision to use digital technologies in the workplace context. This paper additionally contributes to the literature by making a case for the importance of conducting literacy related IS research in workplace context. We also contribute to research stream on literacy by showing that although age character has commonly been used as a denominator to classify individuals as digital natives and digital immigrants and use of digital technology (e.g. Nikou et al., 2019), other influential factors such as perception of IL and DL could be used instead to assess the intention to use technology at workplace context (Paganin and Simbula, 2021). Such findings represent fresh theoretical contributions to the literature on literacy and technology acceptance.

Our research results also provide some practical implications. For example, decision makers and managers should pay a careful attention to their employees' literacy levels. As literacy skills are critical skillset in the digital age, managers or chief information officers may first aim at identifying the work groups or individuals who needs literacy training and then aim at providing specific and relevant training or literacy instruction to enhance those with a low level of literacy. This is important as employees' literacy skills will have a significant impact on organisations that rely on a skilled workforce to stay competitive in the digital age (Farrell et al., 2021). The importance of literacies skills can further be emphasised as interests in such skills in the workplace continues to grow (Forster, 2019), as well as in many workplaces job performance dictates that employees should be competent and keep skills up to date (Ali and Richardson, 2018). Furthermore, the findings of the study may help managers in comprehending how and why IL and DL are important, particularly as new generations enter the workforce. In addition, managers can ensure that their employees' anxiety when encountering new tools is reduced by creating an environment where digital technology engagement can be built and strengthened. This allows them to interact with new technologies more easily and comfortably (Tufts, 2010; Vodanovich et al., 2010). Another implication is that, for managers faced with low literacies amongst their workforce, they should demonstrate the ease of using digital technologies, and not the usefulness of those technologies. In other words, scarce resources should not be spent on convincing workers that a digital technology is helpful for their purposes. Instead, those resources should be spent on teaching how to use the technology or convincing workers that a technology requires little effort to learn.

It is also necessary to discuss the limitations of this research. For example, using self-report to evaluate both dependent and independent variables raise questions regarding the validity of causal inferences due to systematic answer distortions, method variance bias and survey items' reliability and validity. We did, however, control for potential bias by doing rigorous statistical analyses to ensure our data were free of it. Furthermore, the participants studied in this study are assumed to have a high degree of DL and IL skills. This assumption is supported by Sulkunen and Malin's research (2018), who found that, in terms of literacy proficiency, adults in Finland exceed many other countries in the world, including their peers in other Nordic countries. Nonetheless, we recommend that future study include other participants with lower or higher literacy skills who may demonstrate different behaviours on the path relationships proposed in the research model. Further studies could examine how other socio-demographic factors influence the employee's decision to use digital technologies in their workplaces. Finally, while the aim of this study was to look into the impact of IL and DL on intention to use, future studies could look into if using technology increases IL and DL and test whether this assumption is theoretically correct in other words testing the causality. Needless to mention that our sample size was rather small, and future studies with a larger sample size could replicate our research to see if other and different results could be gained.

Figures

Research model

Figure 1

Research model

Conceptual model results

Figure 2

Conceptual model results

Demographic information

NPercentage
Education
High school diploma75.8
Bachelor's degree3730.6
Master's degree6452.9
Ph.D108.3
Other32.5
Type of organisation or industry sector
Public sector (e.g. government)3024.79
Private sector (e.g. businesses, individuals)8066.12
Not-for-profit sector54.13
Other64.66

Proficiency with digital technology/applications at workplace

Digital technology/applicationMean
Microsoft Office5.98
File sharing (e.g. Google Drive, Dropbox)5.72
Mobile devices organiser (e.g. address book, calendar)5.75
Email services (e.g. Outlook, Gmail)6.26
Social media (e.g. Facebook, Instagram)5.62
Microsoft Teams3.79
Skype for business4.97
ERP system2.6

Reliability and validity

ConstructItemsFactor loadingsMeanStdCronbach's αCRAVE
Perceived usefulnessPU10.895.901.220.940.950.81
PU20.935.911.17
PU30.925.881.13
PU40.896.071.06
PU50.856.220.99
Perceived ease of usePEoU10.865.821.140.920.950.72
PEoU20.825.451.24
PEoU30.865.711.11
PEoU40.805.421.19
PEoU50.865.721.14
PEoU60.865.691.19
Digital literacyDL10.895.261.470.930.940.64
DL20.875.691.29
DL30.825.241.41
DL40.805.001.45
DL50.755.791.17
DL60.865.601.34
DL70.726.020.98
DL80.795.691.29
DL90.705.990.99
Information literacyIL10.755.640.930.830.880.59
IL30.745.381.09
IL40.705.171.44
IL50.805.351.33
IL60.855.481.08
Intention to useINT10.766.380.970.920.940.72
INT20.876.520.78
INT30.916.490.81
INT40.896.530.80
INT50.806.590.76
INT60.776.680.72
Attitudes towards useATU10.826.170.930.880.910.68
ATU20.865.741.17
ATU10.815.551.30
ATU20.845.261.30
ATU50.795.731.14

Discriminant validity

ConstructATUDLILINTPEoUPU
Attitude towards use0.82
Digital literacy0.550.80
Information literacy0.530.580.77
Intention to use digital technology0.400.480.460.84
Perceived ease of use0.590.760.680.540.85
Perceived usefulness0.580.480.430.450.530.90

Discriminant validity, HTMT approach

ConstructATUDLILINTPEouPU
Attitude towards use
Digital literacy0.59
Information literacy0.610.66
Intention to use digital technology0.430.520.51
Perceived ease of use0.640.820.770.58
Perceived usefulness0.630.510.470.480.56

Survey items

Digital literacy (Ng, 2012; Serap Kurbanoglu et al., 2006)
DL1I know how to solve my own technical (ICT related) problems
DL2I can learn new digital technologies easily
DL3I keep up with important new digital technologies
DL4I know about a lot of different digital technologies
DL5I have the technical skills I need to use digital technologies for working/learning and to create artefacts (e.g. presentations) that demonstrate my understanding of what I have learnt
DL6I have good digital technology skills
DL7I am confident with my search and evaluation skills to obtain information from the Web
DL8I am familiar with issues related to web-based activities e.g. cyber safety, search issues, plagiarism
DL9Digital technology enables me to collaborate better with my colleagues on project work and other working/learning activities
DL10I frequently obtain help with my work tasks from my colleagues over the Internet e.g. through Skype, Microsoft teams
Attitude towards using digital technology (Ng, 2012)
ATU1I like using digital technologies for working/learning
ATU2I work/learn better with digital technologies
ATU3Digital technologies make working/learning more interesting
ATU4I am more motivated to work/learn with digital technologies
ATU5Digital technologies enable me to be a self-directed and independent worker/learner
Information literacy (Ng, 2012; Serap Kurbanoglu et al., 2006)
IL1When given a work task, I feel confident determining what information I need to search
IL2I am sometimes unsure of how much information I need for solving work related problems
IL3I can easily get my hands-on right information when needed
IL4I understand the organisation of information in my company
IL5When looking for information I can easily identify the right information sources (e.g. organisation’s platforms, colleagues and clients)
IL6I can determine the authoritativeness, correctness and reliability of the information
IL7I am not confident that the information I get is accurate
Perceived ease of use (Davis, 1989)
PEOU1Learning to operate digital technologies would be easy for me at work
PEOU2I would find it easy to get digital technologies to do what I want to do in my job
PEOU3My interaction with digital technologies is clear and understandable
PEOU4I would find digital technologies to be flexible to interact with
PEOU5It would be easy for me to become skilful at using digital technologies
PEOU6I would find digital technology easy to use
Perceived usefulness (Davis, 1989)
PU1Using digital technologies in my job would enable me to accomplish tasks more quickly at work
PU2Using a digital technology would improve my job performance
PU3Using digital technologies would enhance my effectiveness at work
PU4Using digital technologies would make it easier to do my job
PU5I would find digital technologies useful in my job
Intention to use digital technology at workplace (Lin and Lu, 2011; Venkatesh et al., 2003)
INT1I will not hesitate to use digital technologies to access information
INT2I plan to use digital technologies to seek information
INT3I would expect to use digital technologies to seek for information
INT4I intend to use digital technologies to seek for information
INT5I am very likely to use digital technologies to gain information
INT6I will continue using digital technologies in the future
INT7I will recommend my colleagues to use digital technologies

Note(s): Highlighted items were removed from analysis due to low factor loadings

Note

Appendix

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Corresponding author

Shahrokh Nikou can be contacted at: shahrokh.nikou@abo.fi

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