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Journal of Human Resources in Hospitality & Tourism

ISSN: 1533-2845 (Print) 1533-2853 (Online) Journal homepage: https://www.tandfonline.com/loi/whrh20

Preparing Hospitality Organizations for Self- Service Technology

Joseph D. Lema

To cite this article: Joseph D. Lema (2009) Preparing Hospitality Organizations for Self- Service Technology, Journal of Human Resources in Hospitality & Tourism, 8:2, 153-169, DOI: 10.1080/15332840802269791

To link to this article: https://doi.org/10.1080/15332840802269791

Published online: 17 Jun 2009.

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Journal of Human Resources in Hospitality & Tourism, 8:153–169, 2009 Copyright © Taylor & Francis Group, LLC ISSN: 1533-2845 print / 1533-2853 online DOI: 10.1080/15332840802269791

Preparing Hospitality Organizations for Self-Service Technology

JOSEPH D. LEMA Hospitality Management, Drexel University, Philadelphia, PA

Self-service technology is rapidly changing the hospitality indus- try, providing new opportunities for the delivery of services and options for customers. Preparing to implement effective self-service technology delivery programs requires a workforce that can rapidly adapt to change. Understanding factors that influence employee readiness to engage in and support self-directed processes are an important consideration when implementing self-service technol- ogy. The results of the linear regression model in this study indicate that generalized self-efficacy and the self-directed learning readi- ness of employees in the hospitality industry are significantly related variables. While self-efficacy was the most highly correlated vari- able to the self-directed learning readiness of hospitality employees, future studies should consider other characteristics that may influ- ence self-direction. As self-service technology continues to rapidly expand in all areas of the hospitality industry, opportunities and challenges exist for both employees and customers.

KEYWORDS Self-service technology, hospitality, self-directed learning.

INTRODUCTION

Encompassing areas of food and beverage, lodging, and entertainment, the hospitality industry is one of the largest and fastest growing industries in the world, with an enormous amount of human capital investment in a diverse range of jobs. It is estimated that by the year 2014 the hospitality industry will employ more than 14,693 million workers in the United States (U.S. Department of Labor, 2005). With an industry that has one of the largest

Address correspondence to Joseph D. Lema, PhD, Assistant Professor, Hospitality Man- agement, Drexel University, 3001 Market St., Philadelphia, PA 19104. E-mail: [email protected]

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capital labor expenditures in the global economy, the need to focus on the foundation of the hospitality workforce includes an examination of employee development (Erdly & Chatterjee, 2003).

The rapid development of self-service technology is significantly influ- encing hospitality organizations by providing new opportunities and chal- lenges for customers and employees. A Time magazine article reported on the popularity of self-service, with “U.S. customers spending $128 billion at self-service kiosks last year, an 80 percent jump from the year before, and by 2007 it could hit $1.3 trillion” (Kiviat, 2004, p. 101). To maximize learning ca- pacity, self-directed learning readiness is a required strategy to consider with the self-service concept. Self-service allows users greater control over their experience, just as self-directed learning emphasizes the learner’s personal control over his or her own learning experience (Long, 2000).

The skill level and adaptability of employees to initiate change in their jobs are factors in the competitiveness of a hospitality organization. With greater emphasis on productivity and accountability for individual perfor- mance, the responsibility for employees to rapidly adapt to change is moving from an organizational perspective to that of self-directedness. As the hospi- tality industry continues to consolidate, these organizations are experiencing mergers and acquisitions as rapidly as many individual employees change jobs and careers.

Technology in hospitality organizations has provided much of the suc- cess over past challenges with self-service strategies, although human cap- ital investment is required to match the personal characteristics necessary to maximize the full potential of self-service benefits. A recent article in The Economist reported, “Self-service is now doing for the service sector what mass production once did for manufacturing, automating processes and significantly reducing costs” (You’re Hired, 2004, p. 21). With self- service kiosks in hotels, restaurants, and airports, self-service options are becoming a part of everyday life. The explosion of online learning in ed- ucation and business is another example; the result of rapid increases in technology. Although the capacity of self-service strategies is limited by the competency of the user, self-directed learning is at the center of the self-service concept. The purpose of this study was to examine how self- efficacy and selected demographic variables (position, gender, and ethnic- ity) relate to the self-directed learning readiness of employees in hospitality organizations.

Examining whether significant relationships exist among the variables of self-efficacy, demographics, and the self-directed learning readiness of em- ployees in the hospitality industry will have an impact on the productivity and competitiveness of the hospitality industry workforce. Connecting these theoretical relationships in the dynamic and diverse environment of the hos- pitality industry will help link learning theories with emerging practical ap- plications. Examining self-efficacy and demographic variables that influence

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the self-directed learning readiness of employees provides valuable insights into employee learning strategies and human resource development.

As hospitality organizations are required to remain competitive by im- plementing technologies that affect the learning environment of employees, the responsibility for self-directed learning has increased, along with technol- ogy. Characteristics that embrace self-directed learning and those that act as a barrier to self-directed learning need to be examined in order to determine the readiness of an employee to adopt self-directed learning (Long, 1991b). As reported by senior executives within the hospitality industry, some of the overarching issues for organizations include retention, education, training, and recruitment. In addition, positive solutions are needed to help transition employees and adopt strategies that initiate continuous change efficiently in targeted high-growth areas such as the hospitality industry (U.S. Department of Labor, 2005). Peter Senge (1990), known for his “learning organization” theory, reported in his widely referenced book, The Fifth Discipline, that the new learning organization comprises workers who can adapt to change with transformation through motivated self-directed learning and critical thinking.

While technology is fueling the growth of vast amounts of available in- formation, employees are being challenged to apply relevant information in the context of their own work situation. As technology continues to rapidly advance in the hospitality industry and society, it is becoming extremely important to have a highly capable workforce. Developing a competitive workforce is important in a global economy, and it is essential in highly competitive areas such as the hospitality industry. While technology has fueled much of the growth in delivering new services and options that cus- tomers are demanding, a well-prepared and dynamic workforce is required to match the rapidly changing levels of technology.

Motivating employees to initiate change requires preparation and prac- tice. Preparing an employee to be self-directed involves consideration of assumptions that follow self-directed learning methods. An understanding of the theoretical research of the variables that influence self-directed learning readiness will allow a hospitality organization to create effective, efficient programs and practices that maximize the talents of its employees. This unique workforce may have a much greater responsibility to meet the di- verse and ever-demanding needs of customers.

Organizations and employees that promote self-directed learning readi- ness will help prepare their employees to participate in self-directed work teams and support a learning organizational strategy. One of the challenges of this study is to investigate the relationships that selected variables have on self-directed learning readiness. Developing a broader knowledge base of self-directed learning readiness with selected variables may not only ben- efit a people-based business that is highly concentrated in employing and serving people, but other researchers and practitioners may benefit from the unique social learning environment that the hospitality industry has to offer.

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LITERATURE REVIEW

Self-directed learning has been a high-interest topic in the fields of busi- ness and education for more than a decade (Mezirow, 1985). Definitions of self-directed learning share a number of unique and similar perspectives. Although there are a number of unifying elements in defining self-directed learning, there is also a concerning ambiguity in precise definitions among the research (Oddi, 1987). Research into self-directed learning, according to Long (1991a), has developed over the past decade in both quantity and quality. Self-directed learning theory may have received greater attention than the practical aspect, which remains underdeveloped and has not re- ceived the same attention. Brookfield (1984) describes the process of self- directed learning as lacking a full appreciation for the impact of a skillful instructor and may fail to appreciate the social influence of subgroups in the surrounding community or environment. Part of the confusion with the self-directed learning term may be linked to learning as an internal change process and education as an external change process that facilitates internal change (Brockett & Hiemstra, 1991). Rather than moving away from self- directed learning, Brockett and Hiemstra advocate expanding the concept through continued development as a central theme and conceptual frame- work for adult learning.

Self-directedness is a characteristic of adult learning that is closely asso- ciated with self-directed learning and includes a level of decision making and personal control throughout the learning experience. Tough (1979) regards self-directed learning as a form of adult learning that includes the ability to plan and guide the learning process. Adults, according to Tough, have a desire to learn by drawing upon personal autonomy, self-worth, and ac- knowledgment of life experiences. Providing adults the opportunity to direct and plan their own learning builds self-directedness that supports a growing number of adult learning theories (Knowles, 1984/1998; Long, 1991b; Tough, 1979).

Self-Efficacy

Self-efficacy is the belief in one’s own capability to initiate control over situations in an organized process (Bandura, 1994). Expectations of self- efficacy involve psychological procedures which when analyzed may be distinguished as two expectations of efficacy and outcome (Bandura, 1977). “An efficacy expectation is the conviction that one can successfully execute the behavior required to produce the outcomes. An outcome expectation is defined as a person’s estimate that a given behavior will lead to certain outcomes” (Bandura, 1977, p. 79). The differentiation between efficacy and outcome expectations is linked to the learner’s belief that a course of action

Preparing Hospitality Organizations for Self-Service Technology 157

may produce certain outcomes, but the learner questions whether he or she can actually perform those actions.

Bandura (1977) argues that the strength of conviction of the learner’s own belief in effectiveness may determine whether the learner will pursue changing or challenging situations. Learners may fear and avoid challeng- ing situations when their belief is that they will not be able to handle the problem. Conversely, Bandura explains, learners may behave with confi- dence when they judge themselves to be capable of successfully handling situations that would have otherwise been threatening to them.

Self-efficacy theory is based on two types of expectations, mentioned earlier as efficacy expectations and outcome expectations, along with the characteristics, behavior, and behavioral outcomes of the person (Bandura, 1986). Efficacy expectation (self-efficacy) is the person’s confidence in his or her ability to produce the behavior, while the outcome expectation re- sults from the behavior based on a person’s belief about the outcome. Self- efficacy may be a more accurate predictor of performance since outcome expectations are dependent upon self-efficacy (Bandura, 1986). Employees, for example, may be more motivated to perform behaviors that they believe will produce desired outcomes.

Using self-efficacy as a predictor, Bandura (1986) explains, is important in understanding how people function in terms of the choices they make (selection processes), effort (time and persistence), motivation (initiation), thought patterns (cognitive processes), and emotional reactions (affective processes) to various situations. The main sources of information that in- fluence beliefs in self-efficacy include experience of mastery, observation, verbal persuasion, and physiological information (Bandura, 1986, 1997).

One of the most influential sources of information on self-efficacy is experience of mastery (Bandura, 1986). According to Bandura, success and failure attributes are important sources of information for developing self- efficacy. Successful experiences help enhance self-efficacy with a feeling of mastery and control, while repeated failure decreases self-efficacy over time (van der Bijl & Shortridge-Baggett, 2002). When a learner has developed a strong self-efficacy, explains van der Bijl and Shortridge-Baggett, the effect of one failure may not have much influence since the effects of failure follow a total pattern of experiences, although the timing of the moment in the learning process may vary in the power of the effect. If failure takes place in the early stages of the learning process, for instance, the greater will be its negative impact on self-efficacy (van der Bijl and Shortridge-Baggett, 2002).

Bandura (1986) describes a hierarchy in the sources of information for self-efficacy and categorizes them as direct and indirect sources of informa- tion. Experience of mastery, for example, is one of the most powerful sources of information, as a person experiences success or failure immediately based on direct information. The other information sources include observation of others, verbal persuasion, and physiological information based on indirect

158 J. D. Lema

sources of information. Indirect sources of information may not be nearly as powerful in terms of information for self-efficacy as the cognitive pro- cess associated with critically reflective patterns of direct earlier experiences. Other sources that influence self-efficacy include personality traits (Strecher, DeVellis, Becker, & Rosenstock, 1986) such as self-esteem, locus of control, self-confidence, and hardiness (Coppel, 1980), and environmental factors such as expectations and support of others (Bandura, 1986).

In a further theoretical analysis of sources that influence self-efficacy, Gist and Mitchell (1992) suggest that experiences of mastery, observation, verbal persuasion, and physiological information contribute through a vari- ety of internal and external information cues. Internal information cues relate to an individual’s knowledge or skills and the person’s effectiveness in us- ing these skills through various strategies. An individual’s self-efficacy can be determined by an internal assessment (adequate, inferior, or superior) of abilities when performing at various task levels. Judgments about expected performance when engaged in a task can be influenced by mood, health, or degree of arousal, whether positive (excited) or negative (fearful). External information cues relate to the characteristics of the task itself, such as com- plexity, number of components, parts, sequence, uncertainty, and steps. The resources and interdependence required to successfully complete the task can also influence the estimated level of self-efficacy.

Examinations of self-efficacy, Bandura (1997) suggests, often require as- sessments that an individual makes in terms of the variability in influencing determinants, previously described as experience of mastery, observation, verbal persuasion, physiological information, and others. The level of vari- ability may provide sources of information that range from low to high, immediate or over longer periods, stable or unpredictable. Acquiring knowl- edge, for instance, is one factor that may have an immediate effect on an individual, whereas other factors such as ability may change after longer periods of time. Bandura also argues that immediate variability in a factor may result in greater perceived control over those factors that are relatively stable and require longer periods of time.

Bandura (1986) emphasizes that one important element to consider with self-efficacy is the perception of control. Some factors involve personal control (e.g., effort), while other factors are controlled by someone else (e.g., facilitator). The perception that the causes of performance are uncontrollable may result in lower levels of variability, resistance to change, and a lower level of self-efficacy. Bandura claims that analysis and understanding of the individual and task is necessary to enhance self-efficacy.

According to Bandura (1994), self-efficacy involves the belief that peo- ple have in their personal capabilities the ability establish personal stan- dards. Since personal standards may be modified by the environment or demographic characteristics (position, gender, ethnicity), beliefs in personal capabilities may influence possible discrepancies between capabilities and

Preparing Hospitality Organizations for Self-Service Technology 159

self-generated standards. Based on his social cognitive theory, Bandura’s re- ciprocal process of self-efficacy has a primary objective of enhancing learning skills and self-directedness in individuals (Bandura, 1994; Kitson, Lekan, & Guglielmino, 1995).

Self-efficacy theories have created a framework for understanding el- ements related to self-directed learning. Brockett and Hiemstra (1991), for example, developed a two-component model referred to as the Personal Responsibility Orientation (PRO) that supports personal responsibility and individual ownership of the learner’s thoughts and actions or learner self- direction. The other component consists of self-directed learning that em- phasizes the relationship between the learner and facilitator. The PRO model suggests that self-efficacy is central to understanding self-direction in regards to employee learning. The model also suggests that employees are capable of taking a proactive approach to learning and, when given the opportunity to be self-directed, there is the potential to maximize benefits for both the employee and organization.

Another model based on the situational nature of the learner and facili- tator was developed by Grow (1991) called the Staged Self-Directed Learning Model (SSDL). This model assumes that the self-directedness of the learner is based on situational processes. Grow explains that learners progress through stages of self-direction that may either increase or decrease depending upon the situational circumstances. Furthermore, Grow argues, depending on the facilitator’s approach, learning may be supported or hindered in the process. The SSDL model may help to indicate whether a facilitator’s style aligns with the learner’s self-directed learning readiness.

METHODOLOGY

The convenience sample consisted of employees who work in hospitality organizations, with approximately 216 employees participating. Data col- lection occurred at three participating hospitality organizations during April 2006. The participating organizations offer a diverse workforce, with food and beverage, lodging, and entertainment operations representing significant areas of the hospitality organization. A facilitator administered the survey to the employees who volunteered for the study in the participating organi- zations’ business facilities. Completion time for the survey was 30 minutes. Participants were presented with an informed consent form before they par- ticipated in the study which clearly stated the voluntary nature of participa- tion, the ability to withdraw from the survey at any time, and confidentiality of the participants’ identities.

A survey integrating the Oddi Continuing Learning Inventory (OCLI) and Generalized Self-Efficacy Scale (GSE) was presented to the participants as a five-page instrument consisting of 49 questions. The OCLI and GSE

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instruments uniquely complement each other in their generalizability to pro- vide a stable comprehensive indicator of relationships rather than measuring a narrowly defined activity that could be the result of a brief occurrence. Rather than measuring a specific task, the OCLI and GSE measure overall job-related activities. The GSE instrument was used to assess self-beliefs of personal capabilities of the employee (Jerusalem & Schwarzer, 1993). The OCLI instrument, developed as a doctoral dissertation by Oddi (1984), was administered to assess employees’ levels of self-directed learning readiness. The relationships among GSE scores and OCLI scores were examined.

The OCLI survey is one of the most widely reliable and validated in- struments used for the measurement of readiness for self-directed learning (Brockett & Hiemstra, 1991). The OCLI survey measures the level of self- directed learning readiness of adults. With a reported Cronbach’s alpha of.88 and retest reliability of r = .89, the OCLI is an adequately reliable instrument for this study (Oddi, 1984).

Validation of the OCLI instrument was conducted by Oddi, Ellis, and Altman-Roberson (1990) to examine the relationship of the survey constructs and behavioral characteristics that indicate self-directed learning readiness. Three theories were developed to describe the affective, motivational, and cognitive attributes of the self-directed learner. The proactive drive versus reactive drive, commitment to learning versus apathy to learning, and cogni- tive openness versus defensiveness were reported by Oddi et al. (1990) to be the three constructs that emerged. Factor analysis reported by Oddi (1984) indicated that OCLI items contained self-confidence, autonomous learning, and learning with the participation of others. When items were loaded on a general factor analysis, reading avidity and self-regulation emerged as sub- sidiary factors. No factor was related to cognitive openness in the analysis, since scores failed to correlate with the adult intelligence factor. When scores failed to correlate with adult intelligence, discriminate validity was provided. The two other dimensions that Oddi describes as reading avidity and ability to be self-regulating positively correlated with self-confidence, participation, and endurance. These results indicate that the total OCLI score can be used to provide a reliable and valid measure for the construct of self-directed learning readiness.

The generalizability of the OCLI, detailed in a follow-up study by Six (1987), reported that factor analysis across different populations suggested that the factors identified by Oddi (1984) in the development of the OCLI instrument were not unique to the sample. The factor analysis indicated that the factors derived by Oddi did not break up under different study condi- tions to form new factors and, as a result, remained stable across different studies (Six, 1987). Validation of the factor match, Six argued, demonstrates the generality of the instrument across different populations. Respondents circled an answer from a 7-point Likert scale ranging from 1 (strongly agree) to 7 (strongly disagree) to best describe their behavior. The total self-directed

Preparing Hospitality Organizations for Self-Service Technology 161

learning readiness score from the survey was used in the statistical proce- dures as recommended in the literature (Brockett & Hiemstra, 1991; Oddi, 1984).

The GSE consists of a scale designed to measure the generalized self- efficacy or the employees’ belief in their ability to perform their job. Jerusalem and Schwarzer developed the GSE in 1980, and it has been used with thousands of participants in 27 language versions throughout the world (Jerusalem & Schwarzer, 1993). The stability of the GSE has been reported in a number of longitudinal studies along with validation of the instrument in similar occupational and educational environments (Jerusalem & Schwarzer, 1993; Pasveer, 1998; Schwarzer, BaBler, Kwiatek, Schroder, & Zhang, 1997; Schwarzer & Born, 1997; Schwarzer, Mueller, & Greenglass, 1999; Schwarzer & Schroder, 1997). The GSE reports a Cronbach’s alpha of.75, with a retest reliability (after 1 year) of r = .67 and a stability coefficient (after 2 years) of r = .75 (Jerusalem & Schwarzer, 1993). The participant was required to circle the correct response from a 4-point scale ranging from 1 (not at all true) to 4 (exactly true). The overall score of the instrument was calculated by totaling the response score to the appropriate questions. Scoring of the instrument was in accordance with the guidelines provided by the authors (Jerusalem & Schwarzer, 1993).

FINDINGS

Descriptive data for the total sample include position, gender, and ethnicity. The sample consisted of individuals working as supervisors (34%, n = 71) and nonsupervisors (66%, n = 141). In addition, the sample contained 52% females (n = 111) and 48% males (n = 101). Ethnicity included 14% African American (n = 30), 2% American Indian (n = 5), 17% Asian (n = 35), 45% Caucasian (n = 96), 13% Hispanic (n = 27), and 9% Pacific Islander (n = 19). Due to missing responses on the OCLI and GSE, four participants were eliminated from the study. Three participants inaccurately completed responses on the OCLI scale and one participant failed to complete responses on the GSE scale. Consequently the OCLI and GSE scales could not be sufficiently scored for these participants. A total of 212 participants provided an adequate sample size for the number of predictors used in the stepwise multiple linear regression model.

The OCLI variable consisted of a 7-point scale, with a lower number (24 being the lowest possible score) indicating less self-directed learning readiness and a higher number (168 being the highest possible score) repre- senting greater self-directed learning readiness. Scores for the OCLI ranged from a low score of 51 to a high score of 154 with a mean score of 107. The range of OCLI scores in this research were consistent with other research in the area of self-directed learning readiness. The mean OCLI s

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