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Acceptance and Use of SFA of Life Insurance Agents in Thailand:

A Concept Paper

Saranyapong Thiangtam*, Pongpun Anuntavoranich**and Wilert Puriwat***

Acceptance and use of sales force automation (SFA) for life insurance

agents can certainly increase sales productivity, assist in responding to customers’ requests promptly and correctly and also effect on efficiencies of sales-supporting functions in companies in positive ways. In Thailand, there are nearly one million life insurance agents mostly working on commission-based systems, with poor motivation and applying something new without due consideration will normally be unsuccessful. Currently, in order to increase sales productivity, many insurance companies have applied sales force automation and introduced the systems to the agents, but adoption rate of the systems is still low and slow. This research proposes a novel conceptual framework developed from the Technology Acceptance Model (TAM), Task-Technology Fit (TTF), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Social CRM Concepts focusing on customer experience value and co-creation. The proven model will lead to an innovative application of sales force automation combined with Social CRM systems usable through mobile devices for Thai life insurance agents.

Field of Research: Innovation, Marketing

1. Introduction

In order to increase the sales productivity, a number of organizations have developed and information system and tools to support the sales operation. The set of of these tools altogether is called “Sale Force Automation (SFA)”, used to increase efficiency of sales agents in contacting making appointments with customers, sales presentation, and communications such as e-mail correspondence or sales transaction processing system. The system can be applied on wireless system such as laptop computers, tablets or smart phones which accommodates and increases the sales productivity, and also create a professional image for the sales agents and the organization.

Nevertheless, major issue for applying sales force automation is that sales agents do not apply the technology to their works. Cho (2008) proposed a model that indicated sales agents’ resistance to innovation. Furthermore, on January 2nd

, 2013, the author searched the “Science Direct” electronic academic database, using the key words “Sales Force Automation” and “Mobile Technology Acceptance”, for research published during the past ten years (2003-2013) and found 262 articles. Out of these, over forty research published during 2012-2013 studied various factors considered to be impediments to the adoption of the sales force automation. The research also studied academic models related to the adoption of the sales force automation. This clearly indicates the significance of this research issue.

______________________________________________________________

*Saranyapong Thiangtam, Technopreneurship and Innovation Management, Chulalongkorn University. Bangkok, Thailand. Email: saranyapong.t@bu.ac.th

**Asst.Prof. Dr. Pongpun Anuntavoranich. Email: p.idchula@gmail.com

***Dr. Wilert Puriwat. Technopreneurship and Innovation Management Program,Chulalongkorn University, Thailand. Email: drwilert@yahoo.co.uk

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Furthermore, the study by Honeycutt Jr. et al. (2005) which reviewed the past sixteen researches concluded what caused the failure of the sales force automation’s adoption. All of this indicated the issue of sales agents’ resistance to innovation, both in the business of selling industrial goods and consumer goods, especially in the direct sales segment where salesmen are independent businessmen, not personnel under direct supervision of companies. Therefore, in practice, it did not concur with the concept of Cho (2008) that restrictive measures will positively result in the sales agents’ acceptance of innovation.

Negative outcomes of sales team’s rejection to technology adoption are under-utilized sales productivity and inappropriately services customers. Besides, this also created a continuous, negative impact on other interconnected sales support operations.

Positive impact of the sales force automation use: the study of Schafer (1997) (cited in Cascio et al., 2010) evaluated that the sales force automation tools and system could result in the sales increase up to 15-35 percent.

The above mentioned has led to major questions of the study, namely, which factors are educational gaps that affect the sales agents’ technology adoption? In addition to the factors studied and shown in the technology adoption models such as Perceived Ease of Use and Perceived Usefulness, according to the Technology Acceptance Model (Davis et al., 1986 and 1989, cited in Yen et. al., 2010) and the Task-Technology Fit Model (Goodhue and Thomson, 1995 cited in Yen et al., 2010 or the Unified Theory of Acceptance and Use of Technology Model (Venkatesh, 2003), will and how experience value of customers, widely accepted as a critical factor to business management nowadays and in the future, has any influence on sales agents’ technology adoption?

1.1 The Objective of the Research

To study perceived customer experience value and information-task fit, evaluated from customer information, pragmatic information, performance expectancy and effort expectancy which has an influence on sales personnel’s behavioral intention in their acceptance and adoption of the technology.

1.2 Scope of the Research

This research is a quantitative study of which data were collected from 400 life insurance agents in Bangkok and other regions of Thailand during October-December 2013, focusing on the acceptance and adoption of sales force automation via smart phones and tablets. Scope of the study on variables is as follows:

(1) Perceived Customer Experience Value (Gentile et al., 2007), (Nambisan,2010)

(2) Information Task-Fit (Goodhue and Thomson, 1995 cited in Yen et al., 2010), Customer Information and Pragmatic Information

(3) Performance Expectancy (Technology Acceptance Model: TAM (Davis, 1989); Unified Theory of Acceptance and Use of Technology [UTAUT]) (Venkatesh, 2003)

(4) Effort Expectancy (Technology Acceptance Model: TAM (Davis, 1989); Unified Theory of Acceptance and Use of Technology [UTAUT]) (Venkatesh, 2003)

(5) “Behavioral Intention” in “Acceptance and Use” (Unified Theory of Acceptance and Use of Technology [UTAUT]) (Venkatesh, 2003)

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2. Literature Review

2.1 Sales Force Automation

Sales Force Automation (SFA) means tools and information system that support the sales function which involve one or more of following duties:

(1) Increase of sales agent’s individual efficiency such as making appointment with customers, correspondence with customers, data presentation, etc.

(2) Communication such as e-mail correspondence with customers (3) Sales support and sales data processing

Regarding relevant technologies, sales force automation can operate via laptop computers, tablets or smart phones which can be connected via information and communications technology and wireless network.

Sales force automation means applying technology to increase the sales activities’ effectiveness of (Honeycutt et al., 2005) such as arranging appointments with customers and arranging travel routes to meet clients, sales presentation, administrative works, retrieving of information about customers and products, etc. (Widmier, Jackson, & McCabe, 2002 cited in Honeycutt et al., 2005).

As for the adoption of sales force automation, Blodgett (1995) (cited in Honeycutt, et al., 2005) indicated that 55-57 percent of the projects adopting sales force automation failed due to insufficient planning, communications issues, as well as disaccord between the system and sales agents’ needs and objectives, as shown in the following study results:

 The study on sales agents’ technology adoption by Robinson et al., 2005 concluded that major issue for sales agents’ technology adoption resulted from the fact that it took too much efforts to learn or use the technology.

The study on “Antecedents and consequences of CRM technology acceptance in the sales force” (Avlonitis & Panagopoulos, 2005) concluded that the issue for sales agents’ technology adoption resulted from over-expectation of the organization, too much effort required to learn or use the technology and the sales agents’ perception that they did not gain any benefit from the technology.

The study on “Sales technology within the salesperson's relationships: a research agenda” by Tanner & Shipp, 2005, concluded that major hindrance for sales agents’ technology adoption were the conflicting roles of sales agents.

The study on “Sales force technology usage reasons, barriers, and support: An exploratory investigation” by Buehrer et al., 2005 concluded that the problem of sales agents’ technology adoption resulted from too little technological support from the organization, no training and too much effort to learn and adopt the technology required.

In summary, review of the previous 16 relevant studies by Honeycutt et al., (2005) found that the most important obstacle for sales agents’ technology adoption was that it required too much effort to learn and adopt the technology. Second, the sales agents felt that they did not get any benefits from the technology. According to the Technology Acceptance Model (Davis, 1989; Jones et al., 2002), perceived ease of use and perceived usefulness have influence on technology adoption. Furthermore, the sales agents were worried that

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after using the technology, their performance would be too closely followed up or there would be a higher sales target.

The studies on needs and goals of sales agent (Honeycutt et al., 2005) summarized sales agents’ opinions about expectations of benefits from the sales force automation, as follows:

(1) Efficiency or worth for investment means reduced time spent on generating sales revenue or higher sales revenue when compared to the time spent

(2) Competitiveness means the system enable a sales agent to gain a technological edge over others.

(3) Accurate data access means conveniently and accurately accessing to information about products, competitors and target customers.

(4) Improved work system means reduced routine works, especially administrative works that are not directly related to sales function.

(5) Better customer service means better image or better customer perception

(6) Beneficial system for sales function means understanding for sales agent’s work system and effective sales techniques

Sales agents’ views on obstacles for the adoption of sales force automation are as follows: (1) Time spent to learn sales force automation tools means opportunity cost for making

sales

(2) The change may require self-adaptation and loss of independence because after using the technology, sales agents will be closely monitored

(3) Technological risk means waste of time that may result from technological innovations in the future

(4) Other factors such as loss of negotiation power after passing information about customers to the company, loss of teamwork if unable to adjust themselves to new technology or higher expectation of results after adopting new technology

The above literature review about sales force automation can be applied in setting features and functions of the system by taking into account expectations of sales agents who are direct users, expectations of sales supervisors or sales managers who need to monitor the sales agents’ performance. Furthermore, the information also explained major issues why sales agent did not adopt the technology, namely, too much effort required to learn, lack of education to assure them that the sales force automation will give benefits to them and alleviate their concerns that they will be too much monitored and lose power after passing the information about customers to the companies.

2.2 CRM Technology

“Modern CRM” is the idea that an organization collect and analyze data via high-tech information communications technology system (Buttle, 2008 as referred to by Yousif, 2012); there are four important dimensions (1) Strategic CRM which is customer-centered organizational culture (2) Operational CRM which means collaboration of corporate departments who deal with customers, namely, marketing automation and sales force automation that operate via call centers or Internet (3) Collaborative CRM such as interactive system in which customers choose to buy products or services by themselves

and (4) Analytical CRM is the system that analyzes customers’ purchase, evaluates what other products the customers will purchase, reporting and distributing customer database to create value for both customer and business.

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If we evaluate the success of the CRM system by “customer value” obtained from sales figures and profits, it can be concluded that many CRM applications with high-valued investment failed (Bolton & Tarasi, 2006, cited in Yousif, 2012). Gardner Butler Forrester mentioned that during 2001-2009, there was a high failure rate of CRM system due to misunderstanding about CRM system that after investing in the system and software, nothing else needs to be done. The CRM system, therefore, overlooked human factor, change management, work procedure improvement and organizational management (Bolton, 2004 cited in Ozcanli, 2012) including the operator’s rejection to the technology.

People paid a lot of attention to CRM again when Greenberg (2011) proposed that CRM is collaboration, not a one-sided communications from company and also proposed the idea of utilizing the social media. Coupled with Web 2.0 technology, users can create content for real-time communication and interactions; thus, many organizations managed their relationships with customers via online social media, so called social network CRM or social CRM.

2.3 Social Network and CRM

Social network means “group of stakeholders” as well as “relationships” that connect them together. Stakeholders can be a number of individuals separately or together within business units such as department or organization in which stakeholders exchange resources such as data, information, products or services, support and help. Relationships within the social network can be weak or strong, depending on the size and number of participants, frequency of usage, intimacy and exchanged resources (Marsden & Campbell, 1984 cited in Hossain and Silva, 2009).

As for the study on CRM via social network, several research (Lei and Yang (2010); Askool and Nakata (2010); Ang (2011); Green and Starkey (2011); Sigala (2011) cited in Yousif, 2012) studied CRM via social network and concluded that CRM via social network could increase the interactions between the organization and customers, could deeply access to customers and create innovations that place high value on customers and evaluated that participation of customers in social network has an influence on sales agents’ adoption of technology.

CRM via social media is similar to customer self-service in that the enterprise must set up a customer-centered business system and every system must be created for the convenience of customers. In addition, multi-channel services can also help company to save costs. Customer loyalty can be expected from customers’ positive experiences (Bonde, 2010).

2.4 Theories and Studies Related to Co-Creation

Co-creation means joint value creation between company and customers, not the one-sided company’s effort to satisfy customers. In every procedure from identifying problems to finding solutions, there must be collaboration. Companies will focus on creating experiences and product presentation will aim to give experience for each customer. This can be called experience-driven innovation (Prahalad, 2004).

Prahalad (2004) presented the changing relationship between consumers and company under the concept of joint creation, namely, it was a two-way communication, not one-way mass communication like in the past and the communication will move towards customers to company and between customers. Consumers make their own choices and consumers jointly

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create their own experiences under favorable circumstances whereas the “market” will become a space for joint creation of experiences. Ultimately, experience is “brand” which is gradually developed from customer experiences.

This theory is beneficial for this study; it help people understood the value that customers and company obtain when customers participate in company systems including the sales force automation in which there should be a joint value creation between sales agent and customers.

2.5 Customer Experience

“Experience” cannot happen by itself. Creating experience is memory creation. Experience is subjective and internal factor, responding to external factors (Schmitt, 2009).

“Customer experience” is a set of interactions between customers and products, services, organizations or companies that arouse reactions. These experiences are individual relations, in respect to rational, emotional, physical and mental aspects (LaSalle and Britton, 2003; Shaw and Ivens, 2005 cited in by Chiara et. al., 2007).

Customers’ purchase of products is the purchase of experience or hedonic experiences, believing that the particular product will bring happiness (Van Boven and Gilovich, 2003). Customer experience starts at the touch points or contact points, so called “moments of truth” (Carlzon, 1991 cited in Joseph, 1996) between customers and company or what company proposed and all of the experiences are linked to customer engagement (Schmitt and Brakus, 2009).

In conclusion, in marketing, “experience” was the new idea proposed to be a product after presentation of commodity, goods and services became obsolete. Experiences (Prahalad and Ramaswamy, 2004) delivered to customers not only created memory for a particular moment, but must create a continuous great experience of customer with the company (Pine and Gilmore, 1998). Therefore, this was linked with CRM. In this regard, creating a unique experience for customer is not presented by a company, but a joint creation between customer and company via favorable circumstances (Prahalad and Ramaswamy, 2004; Schmitt, 2009). Therefore, role of the enterprise has changed from product presenter to experience deliverer and to the era in which company jointly create value with customers and the enterprise is responsible for creating favorable environment for customers to create their own valuable experience.

2.6 Innovation Adoption

Venkatesh et al. (2003) evaluated and compared existing models of technology adoptions in various aspects including dimension, measurement, sample group, industries sectors, result of studies, hypothesis, significance of technology adoption and relevant variables such as Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM), Motivational Model, Theory of Planned Behavior (TPB), Combined Technology Acceptance Model and Theory of Planned Behavior and Model of Personal Computer Utilization, Innovation Diffusion Theory and Social Cognitive Theory [Sheppard et al. (1988); Davis et al. (1989); Mathieson (1991); Vallerand (1997); Davis et al. (1992),

Venkatesh and Speier (1999); Thompson (1991); Moore and Benbasat (1991); Rogers (1995); Taylor and Todd (1995); Agarwal and Prasad (1997); Karahanna et al. (1999); Plouffe et al. (2001); Higgins (1995); Morris and Venkatesh (2000) cited in Venkatesh et al. (2003)]. After that Venkatesh et al. (2003) used empirical data to analyze and trace

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back to theories to ensure accuracy of different dimensions. Then, Venkatesh et al. (2003) brought together all dimensions and variables to create a new model called Unified Theory of Acceptance and Use of Technology (UTAUT). Variable structure that had an influence on technology adoption included social influence, performance expectancy, effort expectancy, behavioral intention and facilitating conditions.

However, in the “performance expectancy” variable structure, there was a measurement of individual perception that the system would help he or she to work better and the “effort expectancy” variable of Venkratesh (2003) was the evaluation of level of difficulty of technology adoption or namely “perceived usefulness” and “perceived ease of use” of Davis (1989).

This study not only sets major variables from experience value, but also sets the variable framework from the Technology Acceptance Model (TAM) (Davis, 1989) which placed a high importance on perceived usefulness and perceived ease of use (Avlonitis & Panagopoulos, 2005) and included the Information Task-Fit (Goodhue and Thomson, 1995 as referred to by Yen et al., 2010) into the conceptual framework.

As for the study related to industry found that commission-based life insurance agents will adopt the technology due to three reasons: perceived usefulness of new system, attitude towards new system and compatability between the new system and the existing system (Jones et al., 2002 cited in Buehrer, 2005).

The literature review has led to the development of conceptual framework which aims to study variables that affect on life insurance agents’ adoption or rejection of technology, as seen in the details to be discussed further.

3. Research Framework and Hypotheses

3.1 The Model Framework

According to relevant concepts, theories, academic documents and studies, the researcher has created a conceptual framework that displays the relationships of variables and research assumptions, as follows:

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Research Hypotheses

1. Perceived value of customer experience positively affect performance expectancy. 2. Perceived value of joint experience creation positively impact behavioral intention of

technology adoption.

3. Performance expectancy positively affects behavioral intention of technology adoption. 4. Effort expectation affects behavioral intention of technology adoption.

4. Summary

Acceptance and use of sales force automation for life insurance agents can certainly increase sales productivity, assist in responding to customers’ requests promptly and correctly and also effect on efficiencies of sales-supporting functions in companies in positive ways. In Thailand, there are nearly one million life insurance agents mostly working on commission-based systems, with poor motivation and applying something new without due consideration will normally be unsuccessful. Currently, in order to increase sales productivity, many insurance companies have applied sales force automation and introduced the systems to the agents, but adoption rate of the systems is still low and slow. This research proposes a novel conceptual framework developed from the Technology Acceptance Model (TAM), Task-Technology Fit (TTF), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Social CRM Concepts focusing on customer experience value and co-creation. The proven model will lead to an innovative application of sales force automation combined with Social CRM systems usable through mobile devices for Thai life insurance agents.

References

Avlonitis, G. J., & Panagopoulos, N. G. 2005. Antecedents and consequences of CRM

technology acceptance in the sales force. Industrial Marketing Management, 34(4), 355-368.

Askool, S., & Nakata, K. 2010. Scoping study to identify factors influencing the

acceptance of social CRM. Paper presented at the Management of Innovation and Technology (ICMIT), 2010 IEEE International Conference on.

Askool, S., & Nakata, K. 2011. A conceptual model for acceptance of social CRM systems based on a scoping study. AI & society, 26(3), 205-220.

Bonde, A. 2010. Why Collective Intelligence is Essential to Social CRM.

Buehrer, R. E., Senecal, S., & Bolman Pullins, E. 2005. Sales force technology usage—

reasons, barriers, and support: An exploratory investigation. Industrial Marketing

Management, 34(4), 389-398.

Cascio, R., Mariadoss, B. J., & Mouri, N. 2010. The impact of management commitment alignment on salespersons' adoption of sales force automation technologies: An empirical investigation. Industrial Marketing Management, 39(7), 1088-1096. doi:

http://dx.doi.org/10.1016/j.indmarman.2009.12.010

Cho, S. D., & Chang, D. R. 2008. Salesperson's innovation resistance and job

satisfaction in intra-organizational diffusion of sales force automation technologies: The case of South Korea. Industrial Marketing Management, 37(7), 841-847. doi:

http://dx.doi.org/10.1016/j.indmarman.2008.04.004

Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

Gentile, C., Spiller, N., & Noci, G. 2007. How to Sustain the Customer Experience: An Overview of Experience Components that Co-create Value With the Customer.

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European Management Journal, 25(5), 395-410.

Greenberg, P. 2010. The impact of CRM 2.0 on customer insight. Journal of Business & Industrial Marketing, 25(6), 410-419.

Honeycutt Jr, E. D. 2005. Technology improves sales performance—doesn't it?: An introduction to the special issue on selling and sales technology. Industrial Marketing Management, 34(4), 301-304.

doi:http://dx.doi.org/10.1016/j.indmarman.2004.12.002

Hossain, L., & de Silva, A. 2009. Exploring user acceptance of technology using social networks. The Journal of High Technology Management Research, 20(1), 1-18. doi: http://dx.doi.org/10.1016/j.hitech.2009.02.005

Joseph, W. B. 1996. Internal marketing builds service quality. Journal of Health Care Marketing, 16(1), 54-59.

Nambisan, P., & Watt, J. H. 2011. Managing customer experiences in online product

communities. Journal of Business Research, 64(8), 889-895. doi:

http://dx.doi.org/10.1016/j.jbusres.2010.09.006

Ngai, E. 2005. Customer relationship management research (1992-2002): An academic literature review and classification. Marketing Intelligence & Planning, 23(6), 582- 605.

Özcanli, C. 2012. A proposed Framework for CRM On-Demand System Evaluation: Evaluation Salesforce. com CRM and Microsoft Dynamics Online. KTH.

Pine, B. J., & Gilmore, J. H. (1998). Welcome to the experience economy. Harvard business review, 76, 97-105.

Prahalad, C. K., & Ramaswamy, V. 2004. Co-creating unique value with customers. Strategy & Leadership, 32(3), 4-9.

Prahalad, C. K., & Ramaswamy, V. 2004. Co-creation experiences: The next practice in value creation. Journal of interactive marketing, 18(3), 5-14.

Robinson Jr, L., Marshall, G. W., & Stamps, M. B. 2005. Sales force use of technology: antecedents to technology acceptance. Journal of Business Research, 58(12), 1623-1631. doi: http://dx.doi.org/10.1016/j.jbusres.2004.07.010

Schmitt, B., Zarantonello, L., & Brakus, J. 2009. Brand experience: what is it? How is it measured? Does it affect loyalty? Journal of Marketing, 73(3), 52-68.

Tanner Jr, J. F., & Shipp, S. 2005. Sales technology within the salesperson's

relationships: a research agenda. Industrial Marketing Management, 34(4), 305- 312.

Van Boven, L., & Gilevich, T. 2003. To do or to have? That is the question. Journal of personality and social psychology, 85(6), 1193-1202.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. 2003. User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

Venkatesh, V., Speier, C., & Morris, M. G. 2007. User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision

Sciences, 33(2), 297-316.

Xu, Y., Yen, D. C., Lin, B., & Chou, D. C. 2002. Adopting customer relationship

management technology. Industrial management & data systems, 102(8), 442-452. Yen, D. C., Wu, C.-S., Cheng, F.-F., & Huang, Y.-W. 2010. Determinants of users’

intention to adopt wireless technology: An empirical study by integrating TTF with TAM. Computers in

Human Behavior, 26(5), 906-915. doi: http://dx.doi.org/10.1016/j.chb.2010.02.005 Yousif, A. 2012. Towards understanding the added value of social CRM: a systematic

References

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