AN APPRAISAL OF THE ROLE OF CLOUD COMPUTING AS A CHANGE AGENT IN PEOPLE MANAGEMENT

CHAPTER ONE

                                                       INTRODUCTION

                                                          BACKGROUND

Human Resource professionals are an essential part of strategic and organizational leadership adding value by contributing to organizational strategy (Timmons, 2008). The focus of human resource leaders is to identify cost-effective methods for hiring, managing, and developing talent. Minimizing costs, optimizing talent, and positively influencing business outcomes means the HR leader has the opportunity to align with the business as a valuable business partner unlike historical perceptions as a complianceofficer (Chiu & Selmer, 2011). The importance of human resources integration into the business strategy sphere continues to increase since the 1980s (Chiu & Selmer, 2011). Scholars agreed HR, as an important business partner, are becoming increasingly critical to maintain a competitive edge (Kapoor & Sherif, 2012).

Organizational leaders understand that hiring top talent, and retaining talent, is crucial to maintaining a competitive advantage (Aladwan, Bhanugopan, & D’Netto, 2015). The processes of HRM, such as employee recruitment, selection, development, performance, and rewards, are emphasized within a technology-based business environment (Aladwan et al., 2015). The contribution of the Human Resource leader as a value-add business partner includes activities in recruiting and staffing, employee development, performance management, compensation management, and regulatory compliance (Armstrong & Pitrowski, 2006; Eisner, 2010) with influence to organizational performance.

Chiu and Selmer (2011) posited companies that find and retain the best talent have a competitive edge. Staffing a business with top talent is dependent on recruiting, screening, and hiring the right candidate for a specific position against the skills, knowledge, and competencies required for success. The cost to hire and retain top talent is a business goal HR leaders can leverage with new technology (Dickson & Nusair, 2010). While electronic web-based employment practices are widely used, many companies rely on standard HR processes such as recruitment, selection, screening, and performance management (Armstrong & Pitrowski, 2006; Eisner, 2010). Human resource professionals are constantly introduced to technology-based strategies and trends requiring organizational awareness of potential challenges (Morris & Revels,2012; Shilpa & Gopal, 2011). Indecisiveness in managing business operations is an organizational recruiting challenge (Morris & Revels, 2012). Organizations rely on HR leaders to implement solid processes and strategies with integrated technology to maintain an efficient workforce (Morris & Revels, 2012) and department. The objective of HRM is to transform organizational strategy into effective HR strategies that create a competitive edge (Convertino, 2008; Tyson, 1995). In the role of a business partner, the HR leader must add value by providing direction, leadership, and solutions to successfully implement change (Nair, 2011), and achieve business objectives.

Information, technology, and systems have become a critical component in most HR departments for hiring, payroll, training, and other responsibilities (Corsello, 2012). Cloud-Based Computing is expected to intensify the need to change technologies and enable HR to improve performance (Corsello, 2012). Employers use résumés to determine if candidates possess the necessary background, skills, knowledge, and other competencies to warrant investment in more costly selection measures, such as interviews (Cole, Feild, Giles, & Harris, 2008). Digitized portfolios, or e-Portfolios, are tools for students compiling work and identifying how curricular and work activities apply professionally (Eisner, 2010) and are highly encouraged, if not required, by higher learning institutions (Dubinsky, 2003) but not standardized as a tool for talent selection in HR. At the time of this study, some employers use Cloud-Based Computing with social networking and popular websites to screen candidates (Bohnert & Ross, 2010; Marx, 2011; SHRM, 2011; Sprague, 2011; Weiss, 2011); however, most use on-site legacy systems.Recruitment and screening are important processes for organizational success and are transforming slowly through Software-as-a-Service (Deloitte, 2011; Starner, 2011).

Video interviewing is becoming a popular Cloud-based method for conducting interviews in the hiring process (Abardeen, 2012; Banham, 2011; Crenshaw, 2006). Key drivers for implementing video interviewing in the Cloud influence the whole organization including costs, resources, reach, and quality of hire (Abardeen, 2012; Latham, & Luman, 2009), are linked to business outcomes, and driven by the HR leader as a business partner.

Employment recruitment and screening are ubiquitous processes of talent acquisition for human resource professionals (Collins, Domagalski, & Wright, 2011); thereby affecting HR leaders.

Software as a Service (SaaS) will potentially replace traditional software in many departments including human resources (Balbaa, 2011). In all HR leader competency models, the ability to adapt and manage change is a critical success factor (Madu, 2009). According to a survey by Deloitte (2011), standard HR practices in the Cloud are inevitable; however, HR leaders are resistant to implementing Cloud-Based Computing despite their role as an innovative leader, change agent, and business partner, and the potential of using Cloud-Based Computing as a tool to achieve business goals.

The role of a business partner requires competence in diagnosing organizations, reengineering processes, listening and responding to employees, and managing cultural transformation (Loshali & Krishnan, 2013). The HR business partner adds value to a firm through strategy execution, administrative efficiency (Sternberger, 2002), employee commitment, and cultural change (Ulrich, 1997). HR leaders could implement Cloud-Based Computing for HR practices and be willing to influence organizations to use Cloud technologies as an alignment to business strategy (Indranil, 2011).

The HR professional’s perceptions change with the introduction of new or advanced technologies (Polen, 2009) with Cloud-Based Computing being the latest evolution to affect HR professionals. Numerous Cloud-Based Computing applications are available to Human Resource professionals, and more recently to employees and candidates, as technology becomes increasingly sophisticated and accessible (Aljabare, 2012; Indranil, 2011). Organizations are competing for access to a global talent pool, to retain top talent, and require a cost effective platform for conducting traditional talent acquisition processes (Dickson & Nusair, 2010; Kapoor & Sherif, 2012). Existing challenges for large and small businesses substantially invested in fixed behaviors and practices (Gibson, 2012) hinder adoption of new technologies and processes. However, HR leaders need information supporting the decision to incorporate Cloud-Based Computing solutions into effective standard HR processes such as validation from other HR leaders based on experience.

Human resource leaders, as business partners, consider long-term business goals to ensure talent acquisition and development processes align with business strategies resulting in better talent choices (Collins, Domagalski, & Wright, 2011) potentially increasing competitive advantage and organizational performance. Considerations for the study include key drivers, processes, and concerns for implementing Cloud-Based Computing for HR functions, characteristics of an HR leader having successfully implemented Cloud-Based Computing, and the potential effect on HRM and organizational performance. As more companies compete for the finest in the globaltalent pool, and maintaining a competitive advantage (Kapoor & Sherif, 2012), organizations and HR leaders must offer the best opportunity for success when implementing standard HR processes to achieve extraordinary results (Loshali & Krishnan, 2013).

Change initiatives start with leadership; therefore, leaders require adequate preparation for successfully deciding upon, and implementing, changes. Increasing competition for top talent requires organizations to implement effective strategies for hiring from a global talent pool to stay competitive. Human resource leaders are responsible for influencing organizational leadership when implementing HR technology solutions and must have solid support to affect the decision positively (Polen, 2009; Yeh, 2012). The effects of Cloud-Based Computing are slowly evolving despite prevalent interest in its benefits (Willcocks, Venters, & Whitely, 2013). Additionally, a need exists to evaluate the performance of HRM to organizational performance (Fitz-enz & Davidson, 2002; Ulrich, 2010). This study contributes to scholarship, HRM, and leadership by providing information regarding the HR leader’s perspective and insight to their respective experiences implementing Cloud-Based Computing and the potential influence on organizational performance.

The most recent findings include identifying the benefits of Cloud-Based Computing, current HR processes conducted via Cloud solutions, and reasons for slow implementation by HR leaders. Findings include key success factors for technology implementation from industry experts in organizations such as KPMG International, General Electric, LinkedIn, Deloitte, and Sierra-Cedar. Cited throughout this study are foundational theorists in the profession of HR leadership such as Ashbaugh, Rowan,Ulrich, Gibson, and Fitz-enz, and thought leaders in Cloud technology such as Indranil, Luman, Bohnert, Ikhlap, Khan, Mujtaba, Sadiq, and Ross.

Problem Statement

The general problem is the slow adoption of Cloud-Based Computing for efficiency of the HR function (Bersin, 2014; Chen, Low, & Wu, 2011; Deloitte, 2011; Deloitte 2012; Laurano, 2014; Sierra-Cedar, 2015). Bersin (2014) reports a significant gap between organizations considering HR technology an urgent issue and organizational readiness for technology change. Companies all over the world are competing for talent and maintaining a competitive advantage, and must implement strategies and technology for the ability to enhance HR performance and achieve organizational goals (Kaur & Rin Yahya, 2010; Polen, 2009). Consequently, organizations are cautiously implementing new methods for cutting costs and improving efficiency in standard HR processes such as talent acquisition (Toldi, 2010). Traditional hiring practices are extensive and may incorporate different phases, modalities, standards, or strategies, potentially requiring different technologies. Human resource leaders experience resistance to implementing technology-based solutions during the hiring process (Polen, 2009), and in standardized processes, such as the traditional screening interview (Crenshaw, 2006; Evuleocha, 2002) or online résumé.  Globalizing and standardizing processes and technologies are emerging issues in HR (Keebler & Watson, 2014).

Human resource professionals influence organizational leadership when making the decision to integrate technology resources and the factors influencing the organization’s adoption of technology (Polen, 2009; Yeh, 2012). HR technology is a minimum requirement for HR professionals (Madu, 2009) and the adoption of Cloud-Based Computing becomes a competitive advantage in the HR profession (Deloitte, 2011; Yeh, 2012). The specific problem is that the literature does not provide clarity how a more rapid adoption of Cloud-Based Computing will affect HR processes. Human resource leaders should understand the advantages, disadvantages, and risks associated with moving business applications and processes to the Cloud (Wright, 2011), and redefine HR strategies with an understanding of how Cloud-Based Computing can contribute to operational efficiency, revenue growth, and strategic value (Deloitte, 2011). Qualitative studies regarding the factors influencing decisions in HR to adopt technology should be conducted (Bahli, Borgman, Heier, & Schewski, 2013). This study involved using a qualitative method with a Kano research design. The intention of this study was to investigate the reasons HR leaders are slow to implement Cloud-Based Computing, how Cloud-Based Computing influences human resource management and HR effectiveness, and the overall performance of the organization.

Purpose Statement

The purpose of this qualitative study with a Kano research design was to examine how the adoption of Cloud-Based Computing affects HRM and organizational performance. Business executives and HR leaders acknowledge the effect of technology on business processes and strategies, and their influence on technology implementation and adoption (Deloitte, 2011, 2012; Indranil, 2011; Polen, 2009; Starner; 2011).

Additionally, executives, HR leaders, and professionals acknowledge the need for aligning HR and organizational strategies when implementing new technologies to increase business value (Aljabre, 2012; Chiu & Selmer, 2011; Starner, 2011). Balbaa (2011) stated Software-as-a-Service (SaaS) would potentially replace traditional softwarein many departments including Human Resources. According to a survey by Deloitte (2011), standard HR practices in the Cloud are inevitable.

Significance of the Study

Aberdeen (2013) reports 48% of organizations still manually manage and integrate data. Organizations further along the maturity curve are more likely to adopt new technology with 62% of organizations indicating technology will be delivered via cloud within the next two years (IBM, 2015). The adoption of Cloud-Based Computing is slow despite the benefits of its implementation and use (Whitley et al., 2013). The study may be relevant to academia in fields of leadership and HR, the cloud technology industry serving HR, HR leaders as transformational leaders, and leaders of change, HRM, and organizational performance, and in identifying areas for further research, contributing to the HR body of knowledge. Human resource professionals reported to have little knowledge of information systems and HR technology used to facilitate HR activities although HR technology is a minimum requirement for HR professionals (Madu, 2009). An increased understanding and knowledge of HR leaders’ perspectives on implementing Cloud-Based Computing for the HR function could influence HRM and the role of the HR leader as a value-added business partner.

Significance of the Study to Leadership

Transformational leaders strive toward the mutual pursuit of enhanced individual and organizational performance. Transformational leadership contributes to enhancing organizational talent and achieving competitive advantage through people (Birasnav & Dalpati, 2010). Human Resources leads require the technology and tools to manage HR processes effectively (Lombardi, 2014).

The findings from this study contribute to leadership and HR leaders, as transformational leaders, general leaders, and human resource managers, by establishing an understanding of HR professionals’ experience (Maslak, 2008; Nair, 2011) implementing Cloud-Based Computing. Transformational leaders inspire others toward a common vision, encourage innovation (Birasnav, Rangnekar, & Dalpati, 2011; Chen, Lin, Lin, & McDonough, 2012), assist in developing skill sets, led by example, and establish expectations for performance (Bass & Avolio, 1993; Mueller, 2009).  The results of this study benefit transformational leaders in implementing Cloud-Based Computing as an innovative strategy and tool for HRM and the HR function.

The HR leader should be able to identify suitable technology solutions based on organizational priorities and workforce needs (Polen, 2009; Ulrich, 1997; Yeh, 2012). The results of this study benefit HR strategic business partners and professionals, considering a similar strategy, by identifying Cloud-Based Computing applied, concerns, and key success factors of implementing Cloud-Based Computing for HR processes (Deloitte, 2010; Indranil, 2011). A better understanding of HR professionals’ perceptions enhances the potential of the workforce and organization, enriches the organizational leader’s ability to enhance business operations, expands understanding within the HR profession, and assists future research (Polen, 2009).

The study findings contribute to the body of knowledge of leadership in HRM and leadership in general by understanding the perceived effect of Cloud-Based Computing on HRM and HR performance. The results of this study may influence the perspective of HR professionals understanding the characteristics of HR leaders with successful implementation of Cloud-Based Computing, building a business case for moving forwardwith Cloud-Based Computing, and providing a model for implementing Cloud-Based Computing.

Research Questions

More companies are progressively using Cloud technologies for standard Human Resource processes (Deloitte, 2011). Human Resource leaders are business partners and asked to suggest strategies for streamlining standard HR practices. However, Human Resource leaders may be reluctant to move toward Cloud-Based Computing and look to the experience of peers to understand how technologies are implemented and the results of implementation prior to making a technology change. To study the topic of HR leader’s perspective on implementing Cloud-Based Computing, the following research questions guided the study:

RQ1: What are the Cloud-Based Computing tools that appear to be most effective for Human Resources?

RQ2: What are the impediments to adoption of Cloud-Based Computing in Human Resources?

RQ3: How does successful Cloud-Based Computing affect the performance of

HRM?

RQ4: What leadership traits of successful Cloud-Based Computing adopters also contribute to HR performance?

RQ5: How does HR contribute to the overall performance of an organization?

RQ6: What are the implications of best practices in Cloud-Based Computing adoption within HR and to general leadership theory?

Nature of the Study

The conduction of this study involved a qualitative research methodology with a modified Kano research design modified to leverage the strengths of qualitative and quantitative research allowing for insight to subjective and objective issues and determine the HR leader’s perception of the topic (Skulmoski, Hartman, & Krahn, 2007). The Kano method is an exploratory technique of subjectivity (Hall, 2009; Skulmoski et al., 2007) as an iterative process to collect the subjective opinions and feedback of study participants through a series of surveys using small sample sizes (Skulmoski et al., 2007). While studies existed depicting the decision-making process for adopting cloud technologies, benefits of cloud technologies, and the effect of technology in HR, most studies are conducted in countries outside of the United States, and very little research explains how Cloud-Based Computing potentially affects HRM performance or the reasons behind the slow implementation.

The objective for researchers using a Kano research design is to sample a range of diverse views and perspectives (Okoli & Pawlowski, 2004). Modifications to the Kano can occur between studies, however the following definition captures the essence of the Kano method: “The Kano Technique is a method for the systematic solicitation and collection of judgements on a particular topic through a set of carefully designed sequential questionnaires interspersed with summarized information and feedback of opinions derived from earlier responses” (Delbecq, Van de Ven, & Gustafson, 1975, p. 10). For the purposes of this study, the use of the terms Kano, Kano Method, and modified Kano are interchangeable. The research methods considered for the study included quantitative and qualitative. Quantitative research methods require more datafor an effective study on the topic and thus inappropriate for this study given the lack of data available. A review and the consideration of qualitative research designs including Grounded Theory, Phenomenological, Hermeneutics, and Case Study revealed these methods as inappropriate for this study. A modified Kano research design was most appropriate for this study to gather data of subjective judgments, is effective with small samples, and to identify, compare and contrast the success factors from the perspective of the HR leader. Researchers using a Kano research design are interested in understanding the unbiased expressed views of participants to improve understanding of problems, solutions, or opportunities when knowledge about a problem or phenomenon is incomplete (Skulmoski et al., 2007). Modifications to the study included the identification of informed participants opposed to experts, as consensus is not required (Hall & Jordan, 2013). Hall (2009) argued that the level of quantitative analysis possible in later rounds determines if the study should be characterized as purely qualitative, or mixed method; qualitative analysis followed by quantitation, if later rounds are conducted. Some research studies, referred to as modified Kano studies (Hall, 2009), changed from the approach originally developed by RAND Corporation in the 1960s.

A convenience sampling of 14 informed participants with a minimum of 5 years of HR experience was recruited to participate in the study. The study consisted of a two- round pilot study followed by two rounds of a complete Kano study with the full panel of participants distributed through SurveyMonkey®. The first round of the full Kano consisted of demographic, informative, and open-ended questions and concluded with Likert-type scale questions for ranking in the final round. The questionnaire design of each round of the study was built upon the information collected from the previous rounduntil the sufficient information was uncovered (Skulmoski et al., 2007). NVivo10®, Excel®, and SPSS® software were used to discover subtle connections among data providing additional insight and ideas for answering research questions and justifying findings. Significant results were obtained through correlational analysis during Round 2 of this study in an attempt to further understand and triangulate the data. The results of the analysis resulted in additional recommendations for future research provided in Chapter 5. However, given the small sample size and ordinal data obtained, this study did not justify reclassification to quantitative or mixed methods and remains a qualitative study.

The information in this study directly challenges HR leaders with demonstrating discovered characteristics demonstrated by participants of those HR leaders successfully implementing HR while aligning with transformational leadership. The results of this study distinguish leadership characteristics of technology early adopters in HR, and identify issues hindering adoption and that may assist HR leaders in designing effective change management strategies for adopting and implementing Cloud-Based Computing, and may provide the foundation of a model for implementing Cloud-Based Computing or a model for transformational leaders adopting technology.

Population Sample and Criteria

For the purpose of this study, 14 participants were recruited to participate in this study. A requirement of 5 years minimum of HR experience ensured all participants were knowledgeable about HR, not necessarily experts (Hall, 2009). Informed participants included HR leaders, administrators, executives, generalists, and specialists using and not using, Cloud-Based Computing. A selected subset of the populationrepresented the population under study. Participants were recruited from HR-focused LinkedIn forums and Arizona-based HR organizations. In Round 1, 14 participants completed survey with 12 participants completing the Round 2 survey. A convenience sampling technique was appropriate given the number of LinkedIn forums and Arizona- based HR groups considered for research and incorporating a snowball sampling technique to reach other participants through referrals from participants who initially met the study criteria for participation (Christensen, Johnson, & Turner, 2011).

Data Collection

A minimum of 12 participants were targeted with a convenience sampling and a snowball sampling technique was useful as the desired population was challenging to obtain (Christensen et al., 2011) and expectation of participation was low. Twelve participants completed both rounds of the study. Study participants received an e-mail containing an informed consent form with details about the research process, withdrawal procedures, personal risks, and primary intent of the study. Once participants submitted a signed informed consent, each received a link to the Round 1 questionnaire via e-mail.

The data collection process used online surveys housed with SurveyMonkey® for all rounds of the modified Kano research design. Each round of the study was built upon the information collected from the previous round until the researcher uncovered sufficient information (Skulmoski et al., 2007). Participants were able to withdraw from the study at any time before, during, and after data collection. Data analysis did not include information collected from participants choosing to withdraw from the study without their permission for use.

Data Analysis

Data analysis attempted to find commonalities between leader’s perceptions about the implementation of Cloud-Based Computing, HR practices using Cloud-Based Computing, characteristics of HR leaders skilled at adopting Cloud-Based Computing, and the potential influence on HR effectiveness and overall productivity of an organization using NVivo10® and Microsoft Excel® software in Round 1. NVivo10® is a secure, software program specifically for analyzing qualitative and mixed methods research data. The NVivo10® software allows the researcher to import, code, organize, and query data, discover themes, and reflect on outcomes for rigorous support of the research findings. The software is a powerful tool for uncovering subtle connections among data for answering research questions and justifying findings. The use of the NVivo10® software was for analysis of the qualitative data for Round 1 and served to create the questionnaire instrument for the subsequent iteration. Excel® and SPSS® are software packages for descriptive statistical analysis and used for analyzing data from Round 2. Chapter 3 includes specifics regarding sample size and criteria, methodology, research design, instrumentation, and data analysis.

Theoretical and Conceptual Framework

Theoretical and conceptual frameworks present an overview of the foundational theories and concepts related to the study (Leshem & Trafford, 2007). The basis for the theoretical and conceptual framework supporting the study included HRM, leadership, and technology adoption theories and concepts with respect to innovation, performance, behavior, and change management. This study focused on the experiences and perceptions of HR leaders and their influence with implementing Cloud-BasedComputing for HRM and the perceived effect to HRM and organizational performance. Figure 1 provides a visual of the conceptual framework for the study depicting Human Resources as the social system by which innovations are communicated and technology as factors perceived to influence HRM and organizational performance. Figure 2 shows the relationship between the dependent and independent variables for the study.

Figure 1. Conceptual Framework

Figure 2. Relationship Between Variables

Technology is an organizational factor for maintaining competitive advantage (Oliveria & Martins, 2011). Numerous theories existed explaining the adoption, or lack thereof, of new technologies from an individual perspective; however, few were from an organizational perspective and fewer specific to HR and cloud technology. The study uses Rogers’ (2003) theory of Diffusion of Innovations (DOI) and the Technology, Organization, and Environment (TOE) conceptual framework by Tornatzky and Fleischer (1990).

The TOE framework categorizes three contextual groups: technological, organizational, and environmental. The technological context refers to the internal and external factors to an organization such as perceived barriers, mobility, relative advantage, and accessibility to data and applications (Kraemer, Xu, Zhu, 2006). The organizational context describes factors of the firm including size, scope, structure, leadership support, firm culture, and organizational readiness (Bahli et al., 2013). The environmental context refers to the firms industry, competition, and government policy (Chen et al., 2011; Oliveria & Martins, 2011; Wang et al., 2010).

Diffusion of Innovations theory attempts to explain “how, why, and at what rate new ideas of technology spread through cultures operating at the individual and firm level” (Oliveria & Martins, 2011, p. 111). Innovation is communicated through certain channels over time among members of a social system (Rogers, 1995). Organizations adopt innovation that suggests various degrees of resistance effectively visualized as a bell curve with 2.5% considered innovators, 13.5% as early adopters, 34% as early majority, 34% as late majority, and 16% as laggards. Independent variables related to organizational innovation adoption include individual leadership characteristics, internalcharacteristics of organizational structure, and external characteristics of the organization (Rogers, 1995). The diffusion of innovation consists of five characteristics that influence innovation adoption:

• Relative advantage – the degree to which innovation can bring benefits to an organization;
• Compatibility – the degree to which an innovation is consistent with existing business;
• Complexity – the degree to which innovation is difficult to use;

• Observability – the degree to which the results of an innovation are visible to others and;
• Trialability – the degree to which an innovation may be experimented. (Rogers, 2013, p. 15)

The TOE framework and DOI theory align with principles of change management theory and strategies for implementing change in HR (Ruta, 2005) and for HR technology (Benvenuti, 2011; Ruta, 2005).  Oliveria and Martins (2011) conducted a thorough review of research studies using DOI and TOE from an empirical perspective (Kraemer

et al., 2006; Wang, Wang, & Yang, 2010). Wang, Wang, and Yang (2010) and Chen, Low, and Wu (2011) conducted separate studies on Radio Frequency Identification (RFID) and Cloud technology adoption, respectively, using the TOE framework and DOI theory.

Human resource management focuses on theory development, actionable managerial principles, historical origins, and development of management scholarship and practice (Kaufman, 2012). The theory explains how human resource managementpractices align with organizational performance (Huselid, 2011; Kaufman, 2012; Marler, 2012; Wright, Gardner, Moynihan, & Allen; 2005). Thought leaders, in the human resource management field, agree the HR professional must be a change agent, technology proponent, and innovation champion to create value toward organizational performance (Fitz-enz & Davidson, 2002; Ulrich, 1997, 2012).

Transformational leadership is marked by a leader’s ability to influence others (Bass & Avolio, 1993), embrace innovation (Wren, 1995), and guide others toward accomplishing goals and improving organizational performance using the transformational characteristics and behaviors the leader possesses (Birasnav et al., 2011). Transformational leader characteristics in alignment with those required of HRM are professionals as champions of innovation and change, particularly when adopting new technologies (Yost et al., 2011). Previous studies using the DOI theory and TOE framework have an empirical approach to determinants of technology adoption without reference to leadership style and characteristics, not within the HR profession, and limited association to organizational performance. Additionally, the study took a qualitative approach for better understanding of the problem to answer the research questions.

Assumptions

The study involved five assumptions regarding bias, sample size, and participants. Impartiality throughout the study is critical for maximizing understanding (Christensen et al., 2011). One assumption was that the researcher remains unbiased (Linstone & Turoff, 1975; Murray & Hammon, 1995a). Kano is an optimal methodology for small sample sizes (Skulmoski et al., 2007). Given the newness of Cloud-Based Computing in HR,and the resistance to implement these technologies, 17 HR informed participants were petitioned for the study resulting in 14 participants completing Round 1, and 12 participants completing Round 2. Another assumption was the selected method of recruitment through LinkedIn groups and Arizona HR organizations were viable locations for recruiting study participants. Kano rounds may be considered a time- consuming activity. Participants were assumed to have time availability for engaging in the study and commit to completing two rounds of questions.  A final assumption was that study participants responded honestly and candidly, and had the information needed to answer the questionnaire (Salkind, 2003). Participants received assurance of confidentiality and remained informed of the procedures for the study and privacy measures. This study assumed the responses of HR professionals as panelists in the study would mirror those of HR professionals across all industries through the recruitment of participants from various professional backgrounds.

Scope, Limitations and Delimitations

Scope

The scope of this qualitative study with modified Kano research design was an exploration of the perceptions of human resource leaders regarding the reasons for, and against implementation of Cloud-Based Computing. Additionally, the scope included exploring which of the many HR processes used Cloud-Based Computing, what characteristics were common for human resource leaders skilled at implementation of Cloud-Based Computing, and the potential influence of Cloud-Based Computing on HRM and organizational performance.  This study included a convenience sampling of 14 HR informed participants recruited through LinkedIn forums and with expanded reachvia snowball chain method. All participants were confirmed, as required for this study, in having a minimum of 5 years of experience in HR. The full panel of 14 participants responded to two rounds of surveys including open-ended questions, demographic and informative questions, and Likert-type scale ranking questions. The problem is the resistance in adopting and standardizing Cloud-Based Computing for HR. Cloud technologies are vast and services span a variety of technical options including platform, infrastructure, and business processes.

Limitations

Limitations are the boundaries or weaknesses potentially experienced during the study (Leedy & Ormrod, 2010). The validity of the research for a population is a limitation because the design of Kano studies uses small sample sizes (Linstone & Turoff, 1975). Avoiding the urge to oversimplify the complexity of the problem is necessary as the perceptions of participants enhance the outcomes, as consensus is pursued (Linstone & Turoff, 1975). A pilot study occurred to ensure accuracy and reliability of the study results. Suggested revisions to the questionnaires were implemented prior to distribution to the full-panel Kano study participants. Additional limitations to the final study are expounded in Chapter 5.

Delimitations

Delimitations narrow the focus of the study by stating what is not included in the study (Leedy & Ormrod, 2010). The first control was to limit the population to HR informed participants with 5 or more years of HR experience. The second delimitation was to begin recruiting study participants within Arizona-based HR groups and HR- focused LinkedIn forums given the researcher’s location. The implementation of Cloud-Based Computing occurs globally and clients could reside in any location despite their online group affiliation. A snowball sampling effect extended outside of Arizona; however, the sample was limited to organizations primarily based in the United States. Additional delimitations to the final study are expounded in Chapter 5.

Summary

Human resource processes are slowly transforming through the SaaS process (Deloitte, 2011; Starner, 2011). However, HR professionals are slow or reluctant to standardize the implementation of Cloud-based technologies despite the overwhelming agreement of key challenges remedied by Cloud-Based Computing (Deloitte, 2010, 2011; Indranil, 2011; Starner; 2011). The general problem is the slow adoption of Cloud-Based Computing for efficiency of the HR function (Chen et al., 2011; Deloitte, 2011; Deloitte, 2012). The specific problem is the literature is unclear of how effective the HR function may be with the more rapid adoption of Cloud-Based Computing. Human resource leaders must understand the advantages, disadvantages, and risks associated with moving business applications and processes to the Cloud (Wright, 2011).

The theoretical and conceptual framework of the study includes the Technology, Organization, and Environment framework, HRM, transformational leadership, and Diffusion of Innovation theories.  Definitions provided for these concepts and theories are helpful, in addition to the common terms for this research project. Arguments existed that HRM theory is piecemeal (Ferris, Hall, Royal, & Martochhio, 2004); however, the study creates another connection between HR theory, HRM performance, and organizational performance.

This modified Kano study served to provide insight to the perceived effect of Cloud-Based Computing in HR and slow adoption of the technology. Chapter 1 contained information regarding the nature of the study, a review of research questions, scope, assumptions, limitations, and delimitations. Chapter 2 involves a detailed review of the literature applicable to this study, a historical overview, current findings, germinal research, and gaps in the literature.

AN APPRAISAL OF THE ROLE OF CLOUD COMPUTING AS A CHANGE AGENT IN PEOPLE MANAGEMENT