Submitted by Kevin D. Rubel, Dr. Randall Griffiths and Dr. Annette Craven
Abstract
The golf industry has become a highly volatile space due in part to recent economic troubles. Combining an increase in the number of courses with a shrinking number of rounds of golf being played has resulted in competition reaching new levels of intensity. Golf course managers are seeking new ways to respond to the increased competition. Some are introducing new and interesting amenities to retain and attract golfers to their courses. Recently, amenities in the form of new technologies have been developed and made available that aim to enhance the golfers playing experience. Websites now have the capability to provide online tee reservation systems similar to hotel reservations systems that allow golfers to start their game with a minimum of disruptions upon arriving at the course. Global Positioning Systems (GPS) make it easier to see where you are in relation to the hole, how far you are from the green, and which particular club you choose to make each shot. Radio Frequency Identification (RFID) is a new technology that includes putting a transmitter in the ball and using handheld receiver to track the ball, allowing the golfer to find the ball quicker. However the return for investing in these new technologies has not been assessed. The need to assess the impact of this technology is especially important given that the typical golfer is older and my not value the types of technology being implemented. A survey of 56 golfers of all ages, playing levels, and experience was conducted to determine which factors impact a golfer’s choice to play a particular course, with technology being the main focus. The results indicate there are moderate correlations between demographics items and these new technologies. However, these correlations do not provide as much predictability as other factors typically used in customer segmentation. Several interesting significant correlations were found between gender and price as well as gender and location that could be of beneficial use for future study. Implications for golf course practice are discussed.
Introduction
The golf course industry today has become increasingly unstable and highly competitive. Supply and demand continue to recalibrate following the late-2000s financial crisis (7). Although the US golf course industry has grown to include approximately 12,000 establishments with combined annual revenue of about $20 billion, land use restrictions and declines in participation in golf have challenged the industry. The number of people playing golf has dropped nearly 15 percent since peaking in 2005 (6). Increasingly shared family demands, higher cost of play, weather patterns, and the inherent demands of the game have contributed to decreasing the number of rounds played in recent years. These fewer numbers of participants are being offered an increasing variety (3) and quantity of courses from which to choose giving golfers more options.
Competitive markets increase the need to understand what drives a company’s customers. This understanding often begins with demographic investigation. Hennessey et al. (5) sought to update golfer’s demographics as a part of their investigation of decisions to visit and play at a golf destination. They found that the more dedicated golfers (golfers who play more often) were older, wealthier, and were visiting specifically for golf. The infrequent and moderate golfers were more price-conscious whereas the older dedicated golfers were less price conscious.
Usage has also been shown to influence how the customer views the course. Smith and Marco (11) divide golfers into two groups: committed golfers, and non-committed golfers which include new golfers and potential new golfers. Committed golfers are defined as golfers that play at least eight rounds of golf per year, make up about half the total amount of golfers, and represent ninety percent of the dollars spent playing golf. These more experienced golfers will often develop a sense of enduring involvement in their activity if they have a positive experience related to their game of golf and may even have transcendent experiences. In other words golf may be seen by avid golfers as a sacred ritual in their lives (9). A golfer’s choice of where to play has been shown to favor courses associated with sacred feelings and vary based on the involvement of the golfer. Reputation has also been shown to impact a golfer’s perception of a course (8). Reputation was found to be multifaceted and could be increased through variables such as word of mouth recommendations, direct perceptions of quality, and exposure through the media.
Today course managers are no longer seeking competitive advantage solely on the issues of price, location, usage, and reputation. Some golf course managers are responding to the increased competitiveness by leveraging new course technology. The desire is to provide a superior golfing experience and ultimately lead to increasing rounds played at the same course and attracting customers from other courses. The question is whether or not golf participants value these new technologies enough to influence their choice of venue. Betting on technology is even riskier when one acknowledges that the golf population is traditionally made up of an older generation typically resistant to technology adoption. Only 3% of persons older than 75 use a smartphone, only 33% of those persons use the internet, and only 41% even have a computer (10).
Technology has spread into nearly every facet of modern life and golf is no exception. Most technological advances to this point have been geared toward individual golf equipment. Buley (1) discusses the high tech world of golf including how club makers are going back to a physics concept called moment of inertia to improve the performance of golf clubs. Golf balls are specifically designed for the golfer’s swing speed. Shoe manufacturers in addition to comfort and support study the best placement of the spikes on the bottom of the shoe. Companies like Nike continue developing better moisture wicking lines of clothing that are now constructed with UV protection in mind. The golf consumer has become used to the presence of technology through these widely available superior versions of traditional golf equipment.
Courses, however, have been using technology to extend the core product. Evans (2), in an article for the BBC, discusses the popularity of Global Positioning Systems (GPS). While golfers have been using GPS smartphone applications to assist them with club choice, courses are now incorporating GPS systems on their golf carts. These cart based systems seek to be more accurate than the smartphone versions. Radio Frequency Identification (RFID) puts a transmitter inside the golf ball. The golfer can, with a radio receiver, walk right to where they hit their ball. Web-based reservation systems are challenging the traditional phone-based system to make tee times (4). Although use of this type of system increased by 25% in 2012 and several companies are developing and marketing online reservation systems, they only account for 14% of all tee time reservations. Hennessey et al. (5) found that word of mouth was more effective to find a golf destination to play versus traditional marketing or newer high tech marketing. These lack luster results may be an indicator that golfers do not value the inclusion of technology at the course level.
The adoption of these course technologies represents an investment of money, time, and effort by course management. However, this investment remains unproven. Given the typical golfer’s age and associated slow adoption of new innovation, the investment in technology may even be ill informed. This research sought to shed some light on how much golfers value this technology and whether it influences decisions to stay at a specific course or change to another course.
The survey, entitled Emerging Technology and Golf Preference, was constructed and posted to the online survey system Survey Monkey. The survey consisted of questions relating to seven factors identified within the literature as being used in the segmentation of the golf market. These factors included price, location, amenities, customer service, reputation, scheduling website, and advanced technology (GPS carts and RFID balls). Each factor was rated on a five point Likert scale for importance in the decision to choose his or her current course. Each factor was also rated for importance in an imagined decision to switch to another course. Agreement to a statement indicating that they would switch to another course (e.g. I would use a different course regularly if it offered highly interactive website options such as tee reservations, scheduling lessons, coupons, etc.) was also assessed for each factor. The respondent was also asked to rank the seven factors to ensure indication of his or her most important factor. The survey finished with skill questions (e.g. handicap and playing level) and demographic questions (e.g. age, gender, and income).
Initial requests for participants were sent by email to a convenience sample consisting of the principle investigator’s current golf contact list (n=21). Recipients of the email were encouraged to forward to others including golfers of any ability level, individuals indicating they were taking up the game, members of membership clubs, and daily use golfers. These inclusive sample criteria were chosen in an attempt to capture a wide experience level and broad range of perspectives on technology. The email included a request that the principle investigator be included in the email to ensure he had control of the participant count as well as the number of requested participants to track response rate.
Analysis
At the completion of the survey period data was collected from Survey Monkey and entered into SPSS Version 19. Pearson correlations were used to examine associations between demographic items and the seven factors of price, location, amenities, customer service, reputation, scheduling website, and advanced technology.
Results
951 invitations were sent through an email request to participate with an additional request to pass on the invitation to friends and relatives to encourage participation. There were 56 responses. Some of the low response rate can be attributed to invitations being sent to non-golfers that had no desire to participate. The demographics lean toward a stereotypical golfer being older males, with an annual income that is greater than $75,000 per year. Sixteen of the respondents chose not to answer the gender question, and of those that did answer the question 85% were male and 15% were female. Seventeen of the respondents choose not to answer the age question, and of those that answered the question, 74% were over the age of 45. Eighteen of the respondents did not answer the income question and of those that did, 58% earned $125,000 or more and 95% earned $75,000 or more.
The results of the Pearson product-moment correlations between demographic items and the seven factors are shown in Table 1. A moderate negative correlation was found between age and website, r(35) = -.301, p < .10, indicating website importance fell as age advanced. A moderate negative correlation was also found between gender and website, r(38) = -.265, p < .10, indicating women favored website use more than men. No significant correlations were found between the three demographic items and the advanced technology factor. As for the remaining seven factors, a significant correlation was found between gender and price, r(38) = .414, p < .01, indicating men were more price sensitive. A significant relationship was also found between gender and location, r(38) = .478, p < .01, indicating women were more location sensitive.
| Table 1. Correlations of grouped data points | ||||
| Correlations | gender | age | income | |
| Price | Pearson Correlation | .414** | -.134 | -.008 |
| Sig. (2-tailed) | .008 | .430 | .960 | |
| N | 40 | 37 | 37 | |
| Reputation | Pearson Correlation | .005 | .083 | .132 |
| Sig. (2-tailed) | .975 | .627 | .435 | |
| N | 40 | 37 | 37 | |
| Location | Pearson Correlation | .478** | .091 | -.045 |
| Sig. (2-tailed) | .002 | .590 | .793 | |
| N | 40 | 37 | 37 | |
| Website | Pearson Correlation | -.265 | -.301 | .169 |
| Sig. (2-tailed) | .098 | .070 | .317 | |
| N | 40 | 37 | 37 | |
| Advanced Technology | Pearson Correlation | -.167 | -.167 | .060 |
| Sig. (2-tailed) | .302 | .324 | .724 | |
| N | 40 | 37 | 37 | |
| Amenity | Pearson Correlation | .146 | .126 | .170 |
| Sig. (2-tailed) | .368 | .457 | .314 | |
| N | 40 | 37 | 37 | |
| Customer Service | Pearson Correlation | .305 | .186 | .205 |
| Sig. (2-tailed) | .056 | .271 | .223 | |
| N | 40 | 37 | 37 | |
| *. Correlation is significant at the 0.05 level (2-tailed). | ||||
| **. Correlation is significant at the 0.01 level (2-tailed). | ||||
Although not part of the original study design, Pearson point correlations were conducted for each of the three individual items (influence on staying, influence on switching, and rank order) which comprised each main factor with the three demographic items (age, gender, income). The results are shown below in Table 2. In addition to the correlations indicated in the main factor analysis, several significant correlations are found. A negative correlation is found between website for current course and income, r(35) = – 391, p < .05, indicating website importance falls as income rises. A moderate correlation was found between gender and advanced technology for current course, r(38) = .311, p < .10, indicating men favor the advanced technology. For the items related to a choice of a different course one relationship was found. A negative correlation was found between customer service for different course and gender, r(36) = -.334 p < .05, indicating women valued customer service in a decision to switch courses. Within the rank order items, a moderate correlation was found between gender and reputation, r(36) = .312, p < .10, indicating men ranked reputation higher than women.
| Table 2. Correlations for individual data points. | ||||
| Rate the importance of the following factors in choosing the golf course listed in item 1. | Gender | Age | Income | |
| Price | Pearson Correlation | -.409* | .052 | -.015 |
| Sig. (2-tailed) | .011 | .758 | .932 | |
| N | 38 | 37 | 37 | |
| Reputation | Pearson Correlation | -.036 | -.168 | -.246 |
| Sig. (2-tailed) | .828 | .321 | .142 | |
| N | 38 | 37 | 37 | |
| Location | Pearson Correlation | -.168 | .060 | .112 |
| Sig. (2-tailed) | .321 | .726 | .517 | |
| N | 37 | 36 | 36 | |
| Website | Pearson Correlation | .417** | .285 | -.391* |
| Sig. (2-tailed) | .009 | .087 | .017 | |
| N | 38 | 37 | 37 | |
| Advanced Technology | Pearson Correlation | .311 | .048 | -.174 |
| Sig. (2-tailed) | .058 | .778 | .302 | |
| N | 38 | 37 | 37 | |
| Instruction | Pearson Correlation | .130 | .348* | .014 |
| Sig. (2-tailed) | .436 | .035 | .933 | |
| N | 38 | 37 | 37 | |
| Memberships | Pearson Correlation | .233 | -.178 | -.193 |
| Sig. (2-tailed) | .166 | .299 | .260 | |
| N | 37 | 36 | 36 | |
| Amenities | Pearson Correlation | -.007 | .011 | -.019 |
| Sig. (2-tailed) | .967 | .948 | .910 | |
| N | 38 | 37 | 37 | |
| Playability | Pearson Correlation | -.069 | -.068 | .207 |
| Sig. (2-tailed) | .678 | .691 | .218 | |
| N | 38 | 37 | 37 | |
| Customer Service | Pearson Correlation | -.087 | -.168 | -.133 |
| Sig. (2-tailed) | .603 | .320 | .433 | |
| N | 38 | 37 | 37 | |
| If you were to choose a different course, rate the importance of the following factors in making that choice. | Gender | Age | Income | |
| Price | Pearson Correlation | -.203 | -.003 | -.095 |
| Sig. (2-tailed) | .222 | .985 | .576 | |
| N | 38 | 37 | 37 | |
| Reputation | Pearson Correlation | .243 | -.087 | -.190 |
| Sig. (2-tailed) | .142 | .610 | .261 | |
| N | 38 | 37 | 37 | |
| Location | Pearson Correlation | -.291 | .069 | .272 |
| Sig. (2-tailed) | .076 | .683 | .103 | |
| N | 38 | 37 | 37 | |
| Website | Pearson Correlation | .147 | .262 | -.125 |
| Sig. (2-tailed) | .379 | .117 | .462 | |
| N | 38 | 37 | 37 | |
| Advanced Technology | Pearson Correlation | .086 | .190 | -.120 |
| Sig. (2-tailed) | .608 | .260 | .480 | |
| N | 38 | 37 | 37 | |
| Instruction | Pearson Correlation | .158 | .475** | .174 |
| Sig. (2-tailed) | .343 | .003 | .302 | |
| N | 38 | 37 | 37 | |
| Amenities | Pearson Correlation | -.027 | -.137 | -.177 |
| Sig. (2-tailed) | .872 | .426 | .301 | |
| N | 37 | 36 | 36 | |
| Memberships | Pearson Correlation | .210 | -.063 | -.152 |
| Sig. (2-tailed) | .207 | .709 | .368 | |
| N | 38 | 37 | 37 | |
| Playability | Pearson Correlation | -.376* | -.105 | .096 |
| Sig. (2-tailed) | .020 | .536 | .574 | |
| N | 38 | 37 | 37 | |
| Customer Service | Pearson Correlation | -.334* | -.055 | -.093 |
| Sig. (2-tailed) | .041 | .745 | .586 | |
| N | 38 | 37 | 37 | |
| Please rank from most important (1) to least important (7) the following items when choosing where to play golf. | Gender | Age | Income | |
| Price | Pearson Correlation | -.129 | .209 | .085 |
| Sig. (2-tailed) | .441 | .215 | .615 | |
| N | 38 | 37 | 37 | |
| Reputation | Pearson Correlation | .312 | .009 | .036 |
| Sig. (2-tailed) | .057 | .957 | .834 | |
| N | 38 | 37 | 37 | |
| Location | Pearson Correlation | -.485** | -.176 | .001 |
| Sig. (2-tailed) | .002 | .296 | .997 | |
| N | 38 | 37 | 37 | |
| Amenities | Pearson Correlation | -.026 | -.091 | -.141 |
| Sig. (2-tailed) | .875 | .594 | .406 | |
| N | 38 | 37 | 37 | |
| Website | Pearson Correlation | .375* | .157 | .163 |
| Sig. (2-tailed) | .020 | .354 | .335 | |
| N | 38 | 37 | 37 | |
| Advanced Technology | Pearson Correlation | .155 | .194 | .136 |
| Sig. (2-tailed) | .352 | .249 | .421 | |
| N | 38 | 37 | 37 | |
| Customer Service | Pearson Correlation | -.136 | -.179 | -.208 |
| Sig. (2-tailed) | .415 | .290 | .218 | |
| N | 38 | 37 | 37 | |
| *. Correlation is significant at the 0.05 level (2-tailed). | ||||
| **. Correlation is significant at the 0.01 level (2-tailed). | ||||
Discussion
Among the seven main factors, the moderate correlations found between the importance of a course website and a golfer’s age and gender do not provide as much support as other factors typically used in customer segmentation. Stronger relationships were found between gender and price as well as gender and location. The use of demographic categories to segment the golf market has a much longer tradition of industry use and research (5, 10).
The lack of even a moderate relationship with the advanced technology factor may be due to the overlap of this technology in players owned smartphone GPS (2). The presence of cart based GPS could hold less significance to players already satisfied with their own experiences. Further research should investigate the satisfaction of customers with their own GPS experience rather than beginning with the course based advanced technology.
While not as statistically significant, some of the relationships of course technology to demographic items does provide some direction to future research. The negative association between age and website importance confirmed the view that older customers are traditionally late adopters of technology (10). We can expect that not only will younger players become heavier consumers of golf (11) but that their acceptance and use of technology will increase as well.
The associations involving gender also provide some directions for future research. Men were shown to be more sensitive than women to the main factor of price, yet less sensitive to the main factor of location. Women were found to value customer service when considering a move to another course. Men, on the other hand, were more sensitive to remaining at their current course based on reputation. Traditional marketing likely favors a male perspective given the history of men as the primary consumers of golf. Future research should investigate the usefulness of these gender differences in staying or switching courses. Women’s presence in the general market place is growing but they only made up 15% of the sample for this study. The potential growth of women in the golf market requires further understanding the factors most important to women’s course loyalty.
Conclusions
The purpose of this study was to investigate the importance of course based technology to golfer’s decisions to stay at a course they are currently playing or to switch to another course. The moderate associations found between demographic items and course technology factors are not as strong as traditionally used factors such as price and location. The investment represented by these technologies for the course is not currently justified by the results of this study. The moderate association between age and website use does seem to indicate that as younger golfers age that the presence of a course website will also rise in importance.
Application to Sport
Course managers presently considering investing in course based technologies such as website tee reservation systems or cart based GPS systems should consider this an investment in the future. The results of this study indicate that the current population of golfers does not hold these technologies in as high regard as traditional factors such as price and location. Management cannot justify its use as part of a loyalty campaign or marketing campaign at this point. As younger golfers age and represent more of the golf population their expectation of these technologies will likely rise with them.
Acknowledgements
This project was done originally as an assignment for a quantitative research class in the Doctor of Business Administration program at the University of the Incarnate Word with the guidance of Dr. Annette Craven and the authors would like to acknowledge the assistance of Dr. Craven in the process of completion of the project.
References
- Buley, Taylor. (2009, March 25). Golf goes high tech. Forbes Magazine. Retrieved from http://www.forbes.com/2009/03/25/high-tech-golf-technology-lifestyle-golftech.html
- Evans, S. (2011, April 8). Technology helps golf get to grips with smarter future. BBC News. Retrieved from http://www.bbc.co.uk/news/business/12962420
- Fanning, S. F. (2003). Segmentation of golf course markets. Appraisal Journal, 71(1), 62.
- Heitner, D. (2013, June 15). Booking tee times gradually shifting to online marketplace. Forbes Magazine. Retrieved from http://www.forbes.com/sites/darrenheitner/2013/06/15/booking-golf-tee-times-gradually-shifting-to-online-marketplace.
- Hennessey, S. M., Macdonald, R., & MacEachern, M. (2008). A framework for understanding golfing visitors to a destination. Journal of Sport & Tourism, 13(1), 5-35.
- Hoover’s Inc. (2014a). Golf course industry index. Business Challenges. Retrieved from http://subscriber.hoovers.com.uiwtx.idm.oclc.org/H/industry360/businessChallenges.html?industryId=1885.
- Hoover’s Inc. (2014b). Golf course industry index. Trends and opportunities. Retrieved from http://subscriber.hoovers.com.uiwtx.idm.oclc.org/H/industry360/trendsAndOpportunities.html?industryId=1885.
- Humphreys, C. (2011). Who cares where I play? Linking reputation with the golfing capital and the implication for golf destinations. Journal of Sport & Tourism, 16(2), 105-128.
- McGinnis, L. P., & Gentry, J. W. (2004). Examining the mediating relationship of “play” on ritual enduring involvement. Advances in Consumer Research, 31, 405-411.
- Moeller, P. (2012, February, 27). Technology still a big disconnect for older Americans. U.S. News and World Report. Retrieved from http://money.usnews.com/money/blogs/the-best-life/2012/02/27/technology-still-a-big-disconnect-for-older-americans.
- Smith, A. D., & Marco, G. (2004). Strategic perspectives associated with the golf industry. The Journal of American Academy of Business, 5(1/2), 367-373.
