The Influence of New Product Characteristics on Rate of Adoption

Abstract

The five characteristics that influence new product rate of adoption are routinely covered in the Principles of Marketing course. Any particular marketing concept such as relative advantage, compatibility, complexity, divisibility, and communicability may not capture interest or engagement among students who take the course as a graduation requirement. Thus, an active learning activity game was developed to address the lack of participation and understanding. Primary assessment of the activity (n = 300) demonstrated that students found Bidding for Buyers a valuable learning experience by encouraging class participation and student motivation. A confirmatory study (n = 85) also demonstrated that student comprehension of new product characteristics and their influence on rate of adoption using a traditional lecture and Bidding for Buyers was significantly higher compared with just a traditional lecture covering the same material.

Keywords

active learning games diffusion of innovations new product

Marketing educators face the task of keeping students engaged in the classroom environment while providing some assurance that the time spent adds value to the student learning experience. This is particularly the case in the introductory marketing course where students from a variety of business-related majors enroll to fulfill a graduation requirement. Various pedagogical approaches including active learning have been used to address the problem of classroom engagement to help clarify concepts and highlight their application. The research presented here adds to the body of knowledge on active learning by reporting on how well an in-class game in Principles of Marketing met its objectives. The objectives include encouraging class participation, enhancing student motivation, and improving student comprehension.

The objective for players in Bidding for Buyers is to earn the most points by setting the best price for a newly modified portable media device targeted at price-conscious consumers who are part of the early and late majority adopter categories. The objective for instructors is for students to gain a better understanding of how new product characteristics, namely relative advantage, compatibility, complexity, divisibility, and communicability (Rogers, 1962) influence the consumer rate of adoption of new products. This is demonstrated through a direct measure of student learning. The original concept for Bidding for Buyers was adapted from Bill Bigelow’s (2002) Transnational Capital Auction: A Game of Survival.

Literature Review

Student engagement in the introductory marketing course can be rather low as most students enrolled in the course are not marketing majors (Taylor, Hunter, Melton, & Goodwin, 2011). As a required core business course it is usually the nonmarketing business majors in particular that often experience apathy and disconnect in Principles of Marketing (Shanahan, Hermans, & Haytko, 2006). To overcome this challenge, many marketing educators use active learning exercises to increase participation (Yamarik, 2007) often times using specific incentives such as small prizes to heighten interest and effort (Chylinski, 2009; Wooldridge, 2008). Active-learning team-based games in particular are the kind of activities that increase student engagement, regardless of chosen major (Taylor et al., 2011).

Active Learning

Active learning as envisioned in its early development involves engaging students with the course content so that they readily make application of the material (Hamer, 2000). Using this approach increases class participation, student motivation, and student performance (Drea, Tripp, & Stuenkel, 2005; Karns, 2006). Conversely, class participation can also foster active learning (Dallimore, Hertenstein, & Platt, 2006) by using teams (Hernandez, 2002), competitions (Vander Schee, 2007a; Widmier, Loe, & Selden, 2007), or a combination of teams and competitions (Ducoffe & Tucker, 2004; Rundle-Thiele & Kuhn, 2008). Other studies document the benefits to using teams to enhance student learning in marketing education, including exposure to diverse perspectives (Amato & Amato, 2005), enhanced student motivation (Denton, 1994), positive student experiences (Hernandez, 2002), and improved student learning (Lancellotti & Boyd, 2008). Indeed, active participation in general improves the student learning experience (Chylinski, 2010).

One concern regarding active learning is that many research reports document perceived learning by students rather than direct measures of mastering concepts (Karns, 2006). The results of a meta-analysis of self-assessment studies by Sitzmann, Ely, Brown, and Bauer (2010) suggest that when students self-assess their learning in class, it is more of an expression of how they feel about a course rather than how much they actually learn from taking it. This is consistent with the findings of Bacon (2011) where student performance on direct measures of learning was not significant, yet students perceived that their learning was enhanced by the pedagogical approach under investigation.

Confounding results regarding student perceptions of learning can be partially explained by metacognition. High academic achievers are much more aware of what they do not know and thus underestimate their mastery of knowledge. Low academic achievers are unaware of what they do not know and thus overestimate their performance. This makes self-assessment of student learning suspect and limits the reliability of indirect measures such as student perceptions of learning (Clayson, 2009).

A good situation is where a direct measure indicates enhanced student learning even if an indirect measure suggests the contrary. An even better situation is where students demonstrate increased learning via a direct measure and have positive feelings about the teaching approach. They would then be more likely to provide positive feedback on the course evaluation. Although student learning is the primary focus, the extrinsic reward serves as an incentive for faculty who might otherwise resist investing the time needed to adopt teaching strategies such as course evaluations in the merit and promotion process (Albers-Miller, Straughan, & Prenshaw, 2001).

Active learning strategies that students find enjoyable are a starting point for incorporating strategies that will enhance student learning, not just their perception of such strategies. Students view games positively as they have been used to promote active learning for some time (Bergstrom & Miller, 1997; Wells, 1991). Team-based games encourage active learning because students often find team-based active learning valuable and enjoyable (Laverie, 2006). Using games translates to greater student learning provided the activities involved are also challenging and have real-world application (Karns, 2006). Teaching with games has also shown to enhance student understanding of course material (Gremler, Hoffman, Keaveney, & Wright, 2000) and improving critical thinking skills (Ackerman, Gross, & Perner, 2003).

Computer games have advantages in that they can be played with very large classes, remotely, or over a longer period of time (Ironside, Joerding, & Kuzyk, 2004; Day & Kumar, 2010). However, they also can be too complex (Gentry, Burns, & Fritzsche, 1993), create anxiety (Grimley, Green, Nilsen, Thompson, & Tomes, 2011), and lead to student frustration with the technology (Halvorson, Ewing, & Windisch, 2011). The interactivity of a noncomputer, competitive game played in real time for just one class period offers the benefits of other active learning strategies without the limitations encountered with exclusive computer use.

Competitions in particular tend to foster heightened class involvement and motivation to participate (Vander Schee, 2011). These kinds of active learning exercises have built-in flexibility in that they can range from a portion of one class period (Allerd & Swenson, 2006), a full class period with the effects lasting much longer throughout the semester (Vander Schee, 2007b) to a semester-long project (Greene, 2011; Munoz & Huser, 2008). This study describes an innovative competition-based active learning game completed in one class period. The application of active learning is specific to characteristics that influence new product rate of adoption.

New Product Characteristics and Rate of Adoption

The consumer market has been divided into five categories based on when they choose to adopt a new product innovation, namely innovators, early adopters, early majority, late majority, and laggards (Rogers, 1983). Much research has focused on identifying the characteristics of those who belong to a particular category (Donnelly & Ivancevich, 1974; Goldsmith & Flynn, 1992; Klink & Athaide, 2010; Martinez, Polo, & Flavian, 1998; Schreier, Oberhauser, & Prugl, 2007). This is understandable because identifying the characteristics of those in the segment most likely to make the purchase and then influence the purchases of others is a very profitable approach. From a product development perspective, identifying the product characteristics that hasten consumer purchase is also beneficial. Rogers (1962) has described the five characteristics that influence the rate of adoption of new products (Rogers & Shoemaker, 1971).

Characteristics are connected to other marketing concepts such as how the rate of adoption is linked to innovation takeoff, or the speed of making the transition from introduction to growth in the product life cycle (Chandrasekaran & Tellis, 2008). Pricing is connected to new product characteristics, particularly during commercialization or the transition from product development to introduction (Chiesa & Frattini, 2011). Connections can also be made to consumer behavior and social influence later in the growth stage (Du & Kamakura, 2011; Kim & Park, 2011). It is at this point that product modifications, reflected in product pricing can encourage mass adoption, particularly for price-conscious consumers.

Although the terms and the concepts they represent are readily apparent to marketers, they may not be so intuitive to students who have had little exposure to the marketing discipline. When talking about complexity, students may not realize that this characteristic of new products is linked to pricing, consumer behavior intentions and actions, as well as social connectedness of consumers (Goldenberg, Han, Lehmann, & Hong, 2009). For example, consumers indicate that they prefer new products with higher complexity along with a good match for their needs and lower uncertainty. However, when it comes to actual purchase decisions consumers do indeed adopt less complex innovations at a higher rate (Arts, Frambach, & Bijmolt, 2011). Those who do choose more complex products often suffer from feature fatigue, which leads to lower postpurchase satisfaction (Thompson, Hamilton, & Rust, 2005).

Given the high failure rate of new product launches (Schneider & Hall, 2011) it is important for students to appreciate the influence of the five characteristics. Efficiency in product development and deployment is thus heavily scrutinized. Students need to be prepared to engage in that conversation even if their career aspirations are in business but not necessarily marketing in particular. Therefore, it is important to develop a teaching innovation to get students enthused about and increase their comprehension of new product rate of adoption characteristics. Highlighting the early and late majority adopter category with a modified portable media device focuses student attention on mass consumer appeal. Using that scenario as a starting point allows the conversation to easily extend from innovators and really new products to laggards and product failures.

A major challenge may be capturing student interest in the topic at the outset because most students in the Principles of Marketing course only take the class as a graduation requirement (Taylor et al., 2011). The Bidding for Buyers game addresses this concern directly. The objectives for instructors using Bidding for Buyers are to increase class participation, enhance student motivation, and improve student comprehension regarding new product characteristics that influence rate of adoption. Instructions on how to execute the game are provided in the Method section.

Method

Auctions have been used in class to demonstrate how a particular auction process works, such as electronic reverse auctions (Williams & Dobie, 2011). Having students prepare for each round of the silent auction is used in Bidding for Buyers to simulate the consumer buying decision process. Then pricing is used as a proxy for the level of new product development characteristics that influence consumer rate of adoption. Pricing has also been used in other active learning exercises (Ducoffe & Tucker, 2004) and is one area where simply delivering the course content without application limits student understanding of its dynamic nature (Clow & Wachter, 1996). The team-based approach has demonstrated positive student outcomes related to involvement and achievement (Esposto & Weaver, 2011; Geringer, Stratemeyer, Canton, & Rice, 2009; Laverie, Madhavaram, & McDonald, 2008). In Bidding for Buyers these teaching elements were brought together to demonstrate how new product characteristics influence the rate of adoption. The game was executed after a 10-minute lecture covering the characteristics and their influence on new product rate of adoption. No grade or extra credit was offered for participating in the game as this was part of a regular class. The game is usually played one third of the way through a 15-week semester.

Bidding for Buyers Suggested Procedure

The Bidding for Buyers game fits well within a 45-minute time frame. The game is executed with the following time requirements in mind. Game introduction and explanation takes approximately 5 minutes. The first round takes about 10 minutes with the subsequent Rounds 2 through 5 lasting a total of 15 minutes. The debriefing session requires 15 minutes but can last longer depending on the nature of the discussion. To prepare for the activity, create the Score Card in an EXCEL spreadsheet similar to the one provided in Table 1.

Table 1.

Score Card

	Company
	1	2	3	4	5	6	7
Round One
Bid
Rank
Game points
Penalty
Round Two
Bid
Rank
Game points
Penalty
Round Three
Bid
Rank
Game points
Penalty
Round Four
Bid
Rank
Game points
Penalty
Round Five
Bid
Rank
Game points
Penalty
Grand total points

With at least 14 students in the class, let students self-select into seven companies. Ask the companies to form around the classroom, as far away from other companies as possible. This can work with up to 50 students in the class. For larger sections, consider having multiple industries, each with seven companies and list each industry on a separate sheet in the EXCEL workbook.

Then distribute copies of (a) Instructions and Definitions (see Tables 2 and 3), (b) Selling Price List (Table 4), and (c) Auction Record (Table 5). Read the Instructions aloud with students. Emphasize the distinction between selling price and game points. Then review the Selling Price List. Point out that a company earns more game points the more it encourages the rate of adoption of the new innovation. Announce that the three companies (per industry for larger sections) with the most game points will win small prizes (e.g., candy).

Table 2.

Instructions

You are the management team of the new products division in a global technology company. Each of your companies has equal access to the American consumer market. You have been charged with modifying a new portable media device targeted at the lucrative price-conscious early and late majority segments of new product adopters. You must compete with other companies also focused on this segment and each is about to modify their own new product similar to yours. Marketing research shows that you can increase the rate of adoption of your new product modification by offering the following characteristics: high relative advantage, high compatibility, low complexity, high divisibility, and high communicability. However, meeting consumer expectations also adds to cost and thus increases the selling price. Many price-conscious consumers will forego expensive new products. At the same time, new products that are priced very low may be perceived as defective or of marginal benefit. The challenge is finding the best combination of product characteristics to gain consumer confidence and therefore sales from the target market.

There will be a series of auctions to capture the purchasing power of this target market. You win the game by ending up with the most game points after five auction rounds. In this activity it is assumed that innovators and early adopters have already purchased the new product. So you are working with a new product modification targeting the early and late majority of adopters. You must focus on value by balancing product characteristics with selling price. Therefore the company that bids the 4th lowest selling price in a round is awarded 100 game points, the company with the 3rd lowest selling price gets 50 game points, and the company with the 2nd lowest selling price gets 25 game points. The other companies get no points for the round because the focus is on capturing the price-conscious consumer early and late majority. The auction is silent—you do not know until the end of each round who bid what.

Keep in mind that the lower you go with price, the more your product may be perceived by consumers as being cheap. Price-conscious consumers want affordable, easy-to-use innovations, however marginally lower priced products may be viewed as having low quality, being unpopular, or simply a poor investment. That is why the company bidding the lowest selling price does not get any game points. Your company may bid the lowest selling price once. For each time you are the lowest bidder more than once, you lose game points (15 the first time, 30 the 2nd, etc.) as a cheap product penalty.

Table 3.

Definitions

Relative advantage: The degree to which the innovation appears superior to existing products. The greater the perceived relative advantage of the innovation, the sooner it is adopted.

Compatibility: The degree to which the innovation fits the values and experiences of potential consumers. The more compatible the innovation is with the lifestyle and technological infrastructure available to the public, the sooner it is adopted.

Complexity: The degree to which the innovation is difficult to understand or use. The easier the innovation is to use, the sooner it is adopted.

Divisibility: The degree to which the innovation may be tried on a limited basis. The shorter the required service contract, for example, the sooner it is adopted.

Communicability: The degree to which the results of using the innovation can be observed or described to others. The more visible the innovation, the sooner it is adopted.

Source. Adapted from Armstrong and Kotler (2011).

Table 4.

Selling Price List

Relative Advantage		Compatibility
Ind Std Index^a	Selling Price ($)	Feature	Selling Price ($)
−65	10	A. Significant lifestyle adjustment, limited local infrastructure	10
−60	15	B. Significant lifestyle adjustment, moderate local infrastructure	20
−55	20	C. Some lifestyle adjustment, limited regional infrastructure	30
−50	24	D. Some lifestyle adjustment, moderate regional infrastructure	55
−45	27	E. Some lifestyle adjustment, regional infrastructure in place	80
−40	30	F. Limited lifestyle adjustment, moderate national infrastructure	90
−35	33	G. Limited lifestyle adjustment, national infrastructure in place	100
−30	37
−25	40
−20	43
−15	46	Divisibility
−10	49	Feature	Selling Price ($)
−5	52	A. Two-year service contract, no rebate offer	10
0	55	B. One-year service contract, 10-day free trial, no rebate offer	35
+5	58	C. One-year service contract, half rebate offer	45
+10	61	D. Six-month service contract, 10-day free trial, half rebate offer	55
+15	64	E. Six-month service contract, rebate offer	65
+20	67	F. No service contract, 10-day free trial, rebate offer	75
+25	70	G. No service contract, 60-day free trial, rebate offer	100
+30	73
+35	76
+40	79
+45	82
+50	85
+55	88
+60	91
+65	94
+70	97
+75	100
Complexity		Communicability
Rating Index^b	Selling Price($)	Feature	Selling Price ($)
100	10	A. Limited to home use	10
90	14	B. Limited to home use, fashion accessory	25
80	18	C. Can be used in home or auto	40
70	22	D. Can be used in home or auto, fashion accessory	55
60	26	E. Can be used in home or auto, social network provided, fashion accessory	70
50	30	F. Universal use, social network provided	85
40	35	G. Universal use, social network provided, fashion accessory	100
30	42
20	48
15	55
10	60
5	70
3	80
2	90
1	100

Ind Std Index = Industry Standard Index where 0 is equal to the industry average.

Rating Index = Consumer research rating where 1 means minimal learning needed and 100 means several days needed to master use.

Table 5.

Auction Record

Round One	Index/Feature	Selling Price	Round Two	Index/Feature	Selling Price
Relative advantage			Relative advantage
Complexity			Complexity
Compatibility			Compatibility
Divisibility			Divisibility
Communicability			Communicability
Total			Total
Round Three	Index/Feature	Selling Price	Round Four	Index/Feature	Selling Price
Relative advantage			Relative advantage
Complexity			Complexity
Compatibility			Compatibility
Divisibility			Divisibility
Communicability			Communicability
Total			Total
Round 5	Index/Feature	Selling Price
Relative advantage
Complexity
Compatibility
Divisibility
Communicability
Total

For the first round tell students to make their bids in each of the categories and total up their selling price on the Auction Record. Note that this is really the hardest round because students have no way of knowing what the other companies will bid. After each company has submitted its bid, enter the total selling prices in the EXCEL spreadsheet. This should be displayed so the whole class can see the results. Award the game points based on the results as explained in the Instructions. After a minute or so cover up the scoring results until the end of the next round. From this point on, the competition to win, or for small prizes, takes over, and students continue to put together the winning combination of characteristics for their new product modification.

In the event of a tie in selling price in a given round each team with the same selling price earns the appropriate game points. To score ties, stop awarding points once three companies have been awarded game points or you reach the fifth lowest selling price, whichever comes first. After each round of bids (five in total), continue to post the selling prices and award game points for that round. Keep a running total of each company’s game points. After the final round award small prizes (i.e., candy) to the winners and debrief with a discussion based on the questions provided in Table 6.

Table 6.

Discussion Questions

1.	How would you bid differently if the target market was innovators? Laggards?
2.	How should the game point system change if the target market was innovators? Laggards? In either case would there be any point to the game?
3.	With an actual new product innovation which of the five characteristics would contribute the most to selling price? Why?
4.	Which innovation characteristics are more influential for services? Goods?
5.	The lower the selling the price, the less consumers have to commit to try it. Does this aspect of divisibility matter more or less to innovators?
6.	Does communicability matter more to innovators, the majority, or laggards?
7.	How can an innovation offer greater relative advantage and a lower selling price?
8.	Given the target market, is the cheap product penalty an accurate reflection of actual consumer behavior? If no, what would be more appropriate criteria?
9.	Did the average industry selling price over the course of five rounds follow the typical pattern found in the actual marketplace?

Bidding for Buyers Game Execution Rationale

A newly modified portable media device was selected as the product to introduce to the marketplace. The functionality of this kind of product is generically understood well enough so that significant details about the product are not necessary. The focus of the activity was on the new product characteristics, not on product specifications. The newly modified aspect was developed to make the product appropriate to the price-conscious early and late majority adopter categories. Other market segments and the corresponding changes needed in the game to reflect them were addressed in the debriefing session as described in the Discussion section.

The five features were designed to reflect the five new product characteristics that influence rate of adoption, namely, relative advantage, complexity, compatibility, divisibility, and communicability. Relative advantage for example was listed using an Industry Standard Index. This allowed students to see that a measure is quantifiable yet for the sake of providing simplicity in the game, further details are omitted. It also encouraged students to focus on strategy and application more so than feature mechanics. Having students compete in teams strongly encouraged interaction and the incentive to win gave them a collective responsibility to learn the concepts such that they could contribute meaningfully to the team. Those who were unsure of particular elements could seek clarification in the social safety of their own team. Organizing the game with five rounds of bidding was designed to overcome the guessing that would occur if there was only one round. Allowing teams to examine the results of prior rounds encouraged them to set a strategy for future bids. This also encouraged students to anticipate the actions of competitors, very much the situation in an actual marketing setting.

Primary Study

This study was conducted at a small private college over six semesters using 14 sections of the Principles of Marketing course with an average class size of 24.3 (SD = 2.6) taught by the same instructor. A survey asking for student perceptions regarding the effectiveness of the Bidding for Buyers game and debriefing session or the class lecture alone covering the same material was administered during the subsequent class meeting 2 days later. The survey items adapted from Vander Schee (2011) are provided in Table 7. This was done to determine whether the game and debriefing session along with the lecture or just the lecture was viewed more positively in terms of increasing class participation and enhancing student motivation.

Table 7.

Student Perceptions Based on Content Delivery Format (n = 300)

	Game^a		Lecture^a
Survey Item	M	SD	M	SD	Diff.	t	p	Cohen’s d
Encouraged me to participate in today’s class	4.55	0.680	3.29	0.902	1.27	20.43	.000	1.577
Was a positive experience	4.54	0.773	3.61	0.891	0.93	15.68	.000	1.115
I prefer learning concepts using the game/lecture	4.44	0.842	2.84	1.056	1.59	18.16	.000	1.675
Increased my enthusiasm for the course	4.31	0.863	3.30	0.874	1.02	17.05	.000	1.163
Enhanced my learning experience	4.29	0.873	3.61	0.849	0.68	10.43	.000	0.790
Encouraged me to learn the concepts	4.22	0.852	3.73	0.829	0.49	7.81	.000	0.583
Helped me better understand the concepts such that I could explain them to a friend	4.07	0.948	3.67	0.846	0.40	6.02	.000	0.445
Clarified any confusion I had about the concepts	4.06	0.914	3.78	0.912	0.28	4.10	.000	0.307

Level of agreement mean rating with Likert-type scale where 1 = strongly disagree and 5 = strongly agree.

Student responses were recorded using a 5-point Likert-type scale where 1 = strongly disagree and 5 = strongly agree. Students were also asked to provide written comments to elaborate on their quantitative responses. Demographic data such as sex, major, and year of study documented on the survey were tabulated using SPSS. Paired samples t-test analysis was used to see if student responses differed based on content delivery format, namely the game and debriefing session after the lecture or just the lecture. Written responses were coded by the most common themes expressed by the respondents and then tallied for frequency.

Confirmatory Study

In the most recent semester of this study two sections of Principles of Marketing participated in the game and debriefing session following a lecture whereas one section only received a lecture on the same material. A 10-question multiple-choice quiz (see the appendix) was then administered in the next class meeting. The reliability (Cronbach’s alpha) was rather low with α = .517, which is not unusual for a multiple-choice assessment with only 10 items and thus has limited reliability. An independent samples t test was conducted to determine if the game and debriefing period following the lecture was more effective in improving student comprehensive regarding new product characteristics that influence rate of adoption more so than a traditional lecture alone. Effect size analysis using Cohen’s d as a standardized measure was then used to make comparisons between the difference in quiz score (direct measure of learning) and individual survey items (indirect measures based on student perceptions). Each analysis in this study was conducted at the .05 alpha level.

Results

Primary Study

The survey was completed by 300 students. Gender was balanced in survey respondents with 43% female. Most of the students who completed this survey were in a business-related major with 48% in Business Administration, 18% in Accounting, 5% in Marketing, 15% in Other Business, and 14% in Other Non-Business. Self-reported year of study was centered on middle-year students with 13% freshman, 31% sophomore, 47% junior, and 9% senior. Table 7 displays the survey results. Students were asked to provide written comments regarding what they liked or disliked about the game, how the game enhanced their learning, and what, if anything they would change about the game for future classes. Table 8 displays a summary of the themes extracted from the most common comments.

Table 8.

Student Written Feedback Summary

1. What aspects, if any, of the Bidding for Buyers game did you really like?

The competition provided an incentive to master the material (33%)

Working in teams allowed students to help each other increase concept understanding (16%)

Using logic and strategy was required in each round (9%)

Applying the concepts in a simulation made the learning interactive (6%)

Debriefing afterward forced students to demonstrate that they understood the material (5%)

2. What aspects, if any, of the Bidding for Buyers game did you really not like?

None (meaning they liked everything) (53%)

Positive comments provided (even though the opposite was solicited) (21%)

Initial explanation was not clear (13%)

Too much focus on pricing, not product characteristics (13%)

3. What aspects of the Bidding for Buyers game enhanced your learning experience?

Directly using the concepts in the game (35%)

Application to a real-world setting (23%)

Students had to understand the concepts to be successful in the game (19%)

Repeatedly focusing on the characteristics in each round (17%)

4. What, if any, would you change about the Bidding for Buyers game?

None (meaning they would not change anything) (74%)

Positive comments provided (even though the opposite was solicited) (12%)

Be more thorough in the initial explanation of how to play the game (9%)

Deter teams from simply focusing on price and not the characteristics (5%)

As seen in Table 7, the survey items related to class participation clearly indicate that Bidding for Buyers encouraged class participation (M = 4.55) more so than just the traditional lecture (M = 3.29). Students also rated the items Was a positive experience and Enhanced my learning experience significantly higher for Bidding for Buyers compared with the lecture alone. As displayed in Table 8, student responses regarding what they liked about the game frequently addressed increasing participation. Represen-tative sentiments include I liked the game because we used strategy, planning, group orientation, and got everyone involved and The whole mechanics of the game were very engaging.

Table 7 also displays the survey results with items relating to student motivation. In each case the average response was significantly higher for Bidding for Buyers than just the lecture. In general students indicated a preference for the game (M = 4.44) over the lecture (M = 2.84). More specifically they rated Increased my enthusiasm for the course and Encouraged me to learn the concepts significantly higher for Bidding for Buyers as well. Student comments regarding motivation to learn ranged from, I actually had to pay attention since there were prizes involved, to The game got us excited and kept us all involved, and To play the game I had to learn the definitions.

Student perceptions regarding their learning of the material, an indirect measure of learning, as displayed in Table 7 suggests that Bidding for Buyers was a more constructive experience. Students more strongly agreed that the game, Helped me better understand the concepts such that I could explain them to a friend (M = 4.07) compared with the lecture alone (M = 3.67). They also indicated that the game, Clarified any confusion I had about the concepts (M = 4.06) to a greater degree than the lecture (M = 3.78). Student-written feedback supported these general perceptions by specifically addressing improved student performance. An example includes Instead of just listening to the definitions with examples in the lecture we had to directly apply the concepts to the game creating a deeper understanding.

Confirmatory Study

Active learning exercises often do not use assessment to demonstrate that students actually learned anything, particularly in comparison with a more traditional approach (Young, Caudill, & Murphy, 2008). Therefore, in the next class meeting after the game an unannounced 10-question, multiple-choice quiz was administered (see the appendix). The results of that quiz show that those who participated in the game and debriefing period after the lecture scored significantly higher (n = 49, M = 6.49) than those who were only exposed to the lecture (n = 36, M = 4.44), t(83) = 4.72, p < .001.

It is possible that those who experienced the game and debriefing period scored higher on the unannounced quiz because they were predisposed with having higher academic achievement. However, the results of an independent sample t test showed no significant difference in cumulative grade point average between those who were exposed to the game and debriefing period (n = 49, M = 2.99) and those who were only exposed to the lecture (n = 36, M = 2.96), t(83) = 0.34, p = .738. Thus, the difference in quiz scores can be attributed to the pedagogical approach taken in the prior class period.

Effect Size and Constructive Feedback

The data in Table 7 show that the effect size for the first four items on the survey were large (Cohen’s d > 0.8) whereas the next two items were medium (0.5 < Cohen’s d < 0.8). The final two items which represent indirect measures of student learning, namely Helped me better understand the concepts such that I could explain them to a friend and Clarified any confusion I had about the concepts had a small effect size (Cohen’s d < 0.5). The effect size (Cohen’s d = 1.041) for the difference in quiz scores between those who experienced the game and debriefing session after the lecture compared with those who experienced just the lecture was large.

Some students provided constructive feedback regarding potential improvements to the game for future consideration. These included specific recommendations such as allowing the groups to debrief individually before drawing in the whole class, using a line graph instead of just a spreadsheet to show trends in prices, and at times students started to focus on just getting the feature costs to total to a particular price rather than consider the contribution of each characteristic. These suggestions are helpful in getting students to think critically about the game itself during the debriefing session as discussed below.

Discussion

In Bidding for Buyers, students made clear connections between new product characteristics and consumer rate of adoption. Price setting was used a proxy for a more complicated process whereby students could see how new product characteristics influence the rate of adoption. The in-class experience provided a nonthreatening environment where everyone could benefit from the explanations students made with each other in teams and then in the debriefing session with the class as a whole. Having seven teams competing provided an incentive for students to try their best and to really understand the concepts such that they could make ready application. Social loafing, which is a common challenge in group work (Aggarwal & O’Brien, 2008) was also minimized in that the group exercise only lasted for one class period and prizes were used as an incentive. Specific outcomes regarding the game experience and debriefing session are provided below.

Game Experience

To some degree increasing participation occurs naturally when students are assigned to work in teams (Parsons & Lepkowska-White, 2009). However, adding a competitive element helps students focus their energy to reach a common goal. This was certainly the case in Bidding for Buyers as students had an incentive to do well. The fact that this was a competition for one team to win was enough motivation to excel considering the nominal nature of the small prizes (i.e., candy) on the line. Survey results indicate that Bidding for Buyers encouraged class participation and enhanced student motivation. Thus the game met its first two objectives for instructors. Beyond merely viewing the game as enjoyable, students also appreciated the interaction and reflection.

The effects of the game are not only limited to the experience of the class period when the game was played. This type of active learning approach where students become more involved also generates more interest in the course content (Frontezak, 1998; Sautter, 2007). Survey results confirm a similar finding for Bidding for Buyers as the average rating for the survey item, Increased my enthusiasm for the course, was rated significantly higher for the game (M = 4.31) than the lecture (M = 3.30). Benefits can carry on long after the game is finished (Vander Schee, 2007b).

When asked to provide written comments about the game the most common responses as listed in Table 8 centered on the benefits of using a competition (33%), working in groups (16%), using logic and strategy was required (9%), making application of the concepts (6%), and enhanced learning during the debriefing session (5%). Additional representative comments include I liked the group aspect and if I didn’t understand something my peers could show me; I loved working in groups for competition–we worked well together and learned more from each others’ perspectives; It helped me to understand the concepts and what marketers really do, the competition got us all excited about the concepts and kept us all involved; and The debriefing helped me to connect the concepts to my experience.

Debriefing Session

The debriefing session provides a comfortable setting for students to reflect on the experience and dialog about what they have learned (Paladino, 2008; Peltier, Hay, & Drago, 2005). This is where students have the opportunity to demonstrate what they have learned and to seek clarification about concepts that still may be unclear. In this case, analyzing various aspects of the game itself was instrumental in making application of the new product rate of adoption characteristics.

The debriefing session included nine questions, listed in Table 6. The first two questions ask about player and game rule modifications based on a different target segment. Students who understand characteristics associated with Innovators quickly determine that maximizing new product features is advantageous. Thus, the scoring in that case should be modified to reflect the most points going to the highest bidding price. For any team that did not figure out the strategy in the first round would certainly do so in the second and, thus, with every team bidding the highest possible price there would be no point to the game. The same scenario would play out for the Laggards category with the focus and scoring rewards on the lowest bidding price. This helps students see the logic behind the scoring used for the price-conscious early and late majority adopter category.

The third question in the debriefing session asks about which of the five characteristics contribute most to the selling price with an actual new or newly modified product. Students provide various responses, however at some point the dynamic nature of Relative advantage is noted. Thus, it is a continuous cost center as companies strive to match any improvement developed by competitors. This conversation is revisited in Question 7 which asks about how an innovation can offer greater relative advantage and a lower selling price? Concepts regarding market penetration and economy of scale from a previous chapter are revisited to explain how this can be accomplished. Students often spend time discussing which of the other four features can be compromised in favor of relative advantage, which is often related to the product category.

The Cheap Product Penalty is addressed in Question 8. Students typically agree that a difference in price by a few dollars does not really dissuade customer purchase. Consumers will only have feelings of deficiency, lack of popularity, poor service support, or outdated model when the product is priced marginally less than competitors. Thus, the penalty should only be enforced when the lowest bidding team is at least 20% lower than the next lowest price bid. This would be applied to any round, not just after the first time a team qualifies for it. Rather than actually change this rule for future administrations of the game, it is helpful to retain it for the sake of providing a lively discussion regarding its application in the debriefing session.

In addressing the last debriefing session question the instructor shows the average selling price per round. The typical pattern is for the price to lower round by round with the fourth and fifth rounds rather close. Although this can vary every time the game is played, regardless of the pattern, it can lead to a fruitful discussion regarding pricing with new products or newly modified products introduced to the market. Not only does this make the activity more realistic, it provides another opportunity to review concepts related to gaining market share, consumer perceptions, and pricing.

The debriefing session is an integral part of the activity. The game itself provided a relaxed, yet competitive atmosphere to enthuse and engage students in the learning process. And in the same spirit as the activity by Makienko (2009), Bidding for Buyers helped students transition from a mode of memorization to one of understanding and application. Again, the debriefing session in particular afforded students the opportunity to demonstrate their understanding of the material by making application to other settings.

Measures of Student Learning

The results of the student survey also indicate that students perceived an increase in their understanding of the concepts. Results of the quiz administered in the next class meeting confirmed student perceptions as students who participated in Bidding for Buyers scored significantly higher than those who only experienced a lecture covering the same material. This is a notable finding compared with other studies where students were indifferent about their participation in a simulation game or found it more enjoyable but then they did not perform any better than a control group of students who covered the same material in a regular format (Bobot, 2010; Dolvin & Pyles, 2011; Grandzol & Wynn, 2011). The game met its third objective for instructors regarding demonstrated student learning and thus makes Bidding for Buyers a valuable teaching tool in marketing education.

Students had no cues regarding their learning from the activity when they completed the survey. Nor did they know that they would be assessed on the material the next time the class met. This may partially explain why the indirect measures of student learning, namely the last two survey items were small compared with the standardized direct measure (i.e., quiz scores). The absence of cues regarding actual learning may explain why the results here are contrary to those found by Bacon (2011) where students perceived that they increased their learning but the direct measures of such learning proved the contrary. Thus, student perceptions may be influenced by performance feedback. When none is offered they do not have any external reference for comparison. Given the high level of engagement and enjoyment, students may assume that these active learning approaches are too fun to be educational.

Another consideration worthy of discussion is the time on task. Students who only experienced the lecture spent approximately 10 minutes covering the characteristics and their influence on new product rate of adoption. Students in the experimental group spent an additional 45 minutes covering the material via the game and debriefing session. Thus, it is possible that the additional time dedicated to covering the concepts may account to some degree for the increase in direct measures of student learning. The fact that students found this additional time an enjoyable experience helps explain the positive outcome regarding the indirect measures of student learning even though the standardized effect size was small.

Hamer (2000) suggests that experiential learning activities should be more broad based, give students greater control over their learning, and endure longer than a traditional lecture. The Bidding for Buyers game is reflective of these requirements in that students were engaged, used concrete examples of the concepts, and spent more time on task than they would simply listening to an explanation from the instructor. The debriefing session provided further reflection on the concepts and their application in the game and then to the real-world setting. This process helps to focus students on the learning objectives of the activity (Hatcher & Bringle, 2000), in this case, increased comprehension of the characteristics that influence the adoption rate of new products.

The game also fostered elaborative verbal rehearsal where students were encouraged to not only remember the important points regarding the concepts with repetition but also to be creative in their selected strategy to perform at a higher level as a team (Simpson, Olejnik, Tam, & Supattathum, 1994). They were then instructed to explain their rationale among teammates to demonstrate that they understood the concepts. Although this was not assessed directly, student comments suggested that the degree to which this took place varied by team. Even though some students may not have consciously processed that they were using a particular technique to increase their learning, they did in fact achieve so as demonstrated on the direct learning assessment.

The results of this study are significant but there are things to consider when making direct application to the Principles of Marketing course. The study was limited to one institution and one instructor using the game for six semesters. The primary study may suffer from retroactive construction of details to conform to the implicit appraisals in that students provided their perceptions of the two teaching approaches only after both were complete. Thus students may remember the lecture less favorably as a result of experiencing the Bidding for Buyers game and debriefing session after the lecture. The increased time devoted to mastering the concepts in the experimental setting may also confound the results as time on task is not accounted for in the analysis. The confirmatory study assessing student comprehension was also limited to only 85 students. Perhaps with a larger pool of students the results could be more generalized.

One concern that came up in the written comments was that some students focused more on price than on applying the five characteristics to the bidding situation. To address this in the future, the instructor will require a logical explanation regarding team strategy from the winning teams as a requirement before actually awarding the prizes. Other future research could focus on adaptation to an upper level undergraduate marketing course or assessment in larger class sections. Students could also be asked to modify the rules to more accurately reflect an actual marketplace where modified new products are introduced and then play the game a second time with the rule modifications in place. Finally, assessment of student learning could be enhanced by increasing the reliability of the unannounced quiz.

Conclusion

Active learning exercises can require more commitment from instructors; however, the outcomes regarding student participation and engagement are worth the time and effort put into their development and execution. In this study students found the Bidding for Buyers game increased their participation and interest in the course material. This can have a carryover effect to other in-class learning situations (Vander Schee, 2007b). However indirect measures, such as student perceptions have not demonstrated actual learning in previous studies (Bacon, 2011; Clayson, 2009). The demand for direct measures will likely not decrease over time as various entities expect greater accountability in higher education.

The Bidding for Buyers game demonstrated an increase in student learning using a direct measure even though the standardized effect size of the indirect measure was not as strong. This provides benefits to students who find the activity a positive experience and display a greater mastery of the concepts. The benefit for instructors lies in having students enjoy the classroom experience which can translate into higher student evaluation of teaching. The positive student learning outcomes should serve as an impetus for future research regarding active learning classroom activities and direct measures of student learning.

Footnotes

Appendix

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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