Maryse Koehl

Juliet F Poujol

John F Tanner

The impact of sales contests on customer listening: an empirical study in a telesales context

Keywords: sales contests, customer listening, call center, telesales

Companies often use sales contests to achieve short-term objectives to motivate salespeople and to boost sales. However, sales contests also may encourage salespeople to adopt less relational behaviors and limit their ability to manage customer relationships, as manifested in their customer listening practices. Therefore, this study, based on a natural field experiment, examines the effects of a sales contest on customer listening. In so doing, four dimensions of customer listening (passive, active, adaptive, and assertive listening), associated with a process of listening (Hearing, Processing, and Responding), were identified. The study helps clarify the effect of a sales contest on these four dimensions of customer listening by telesales agents. The results reveal that this sales contest exerts negative effects only on the active and passive customer listening, not on the adaptive and assertive customer listening. The study sheds light on how sales contests influence important behaviors such as customer listening, as well as on the nature of customer listening itself.

Adapting to the customer is a principal component to building strong relationships, whether adapting the content of a sales presentation to a customer's needs or the style of the presentation to a customer's social style or both (e.g. [START_REF] Castleberry | Selling: Building Partnerships 9e[END_REF]. Customer listening is a foundation to adaptation. A salesperson cannot be customer-oriented unless he/she

(1) develops a good understanding of customer needs through effective listening [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF][START_REF] Baroom | Relational Communication Traits and Their Effect of Adaptiveness and Sales Performance[END_REF], (2) analyzes and understands customer problems [START_REF] Leong | Knowledge Bases and Salesperson Effectiveness: A Script-Theoretic Analysis[END_REF], and (3) tailors products and services to meet customer needs and solve their problems [START_REF] Saxe | .O Scale: A Measure of Customer Orientation of Salespeople[END_REF][START_REF] Baroom | Relational Communication Traits and Their Effect of Adaptiveness and Sales Performance[END_REF]. (Pelham and Kravitz 2008, 415) Yet to date, little research has examined the effects of common sales management practices, such as sales contests, on customer listening.

While research has examined the effects of compensation plans on listening [START_REF] Aiello | Electronic Performance Monitoring and Social Context: Impact on Productivity and Stress[END_REF][START_REF] Roman | The Influence of the Compensation System and Personal Variables on a Salesperson's Effective Listening Behavior[END_REF], sales contests provide the opportunity for field experimentation due to their relative brevity. Sales contests tend to influence salespeople to be sales-oriented rather than customer-oriented, inciting salespeople to achieve specific sales objectives over a short time period. Researchers have identified outcomes contrary to developing relational benefits, such as aggressive sales techniques, overstocking customers, and being less reactive to customer's demands [START_REF] Murphy | In Pursuit of Short-Term Goals: Anticipating the Unintended Consequences of Using Special Incentives to Motivate the Sales Force[END_REF]. Even when contests are designed to avoid these negative consequences, incentives may alter salespeople's customer orientation and long-term orientation [START_REF] Garrett | Customer Value Impact of Sales Contests[END_REF][START_REF] Poujol | The Impact of Contest on Salespeople's Customer Orientation: An Application of Tournament Theory[END_REF] and then indirectly influence the development of the customer relationship.

Customer listening is an important relational component because of its influence on customer trust and satisfaction [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF][START_REF] Aggarwal | Salesperson Empathy and Listening: Impact on Relationship Outcomes[END_REF][START_REF] Drollinger | Salesperson's Listening Ability as an Antecedent to Relationship Selling[END_REF]. Notwithstanding the importance of listening, customer listening remains insufficiently studied in sales force management research, especially in telesales where its practice is so crucial. In fact, only one study has examined customer listening in a call center context: De Ruyter and [START_REF] De Ruyter | The Impact of Perceived Listening Behavior in Voice-to-Voice Services Encounters[END_REF] show the importance of listening behavior in a call center and their positive impact on customer satisfaction, trust, and loyalty. That study, however, examined customers' perceptions of salesperson listening, rather than actual listening behavior. In this study, we leverage a natural field experiment to evaluate listening of telesales agents.

We first review literature pertaining to the concept, modalities, and effects of sales contests, according to a relational perspective, then provide the conceptual background of customer listening. Following our presentation of the study framework, the results of a natural field experiment involving call center salespeople are presented and implications for management and research are discussed.

Literature review

The sales contest: a relational perspective Companies frequently rely on sales contests, short-term incentives to raise sales efforts [START_REF] Lim | Designing Sales Contests: Does the Prize Structure Matter?[END_REF] because they encourage salespeople to achieve a specified goal. From a researcher's perspective, though, contests provide a short-term alteration in control systems (e.g. [START_REF] Anderson | Perspectives on Behavior-based versus Outcome-based Sales Force Control Systems[END_REF][START_REF] Miao | The Interactive Effect of Sales Control Systems on Salesperson Performance: A Job Demands-Resources Perspective[END_REF], thus giving an opportunity to examine the influence of the contest on behaviors and important outcomes in a field setting. [START_REF] Murphy | Sales Contest: A Research Agenda[END_REF] explain that this managerial tool offers a stimulus for performance beyond that generated by a regular salary. The precise objective of the sales contest often aligns with existing goals, such as achieving sales quotas. By nature, sales contest correspond to an outcome-based sales control system [START_REF] Anderson | Perspectives on Behavior-based versus Outcome-based Sales Force Control Systems[END_REF]. Given that sales contest focus on shortterm goals, there is a tendency to concentrate on immediate rather than long-term goals [START_REF] Anderson | Perspectives on Behavior-based versus Outcome-based Sales Force Control Systems[END_REF]. As a result, the challenge is to design a contest that balances motivation against possible negative outcomes such as anti-relational behaviors.

Sales contests have distinct characteristics and modalities, including (1) the nature of their objectives (quantitative or qualitative), (2) the competition format (collective or individual), (3) the budget (open, with a threshold to reach, or closed, with a fixed ranking of winners), (4) the number of winners (low or medium), (5) the type of reward (monetary or not, structure of the reward), (6) the duration (short, medium or long), and (7) the frequency (low or high). These different characteristics and modalities in turn may affect how sales representatives perceive and react to customers. Prior research has identified which modalities salespeople tend to prefer and those likely to motivate, but few has considered the effects different modalities have on relational behaviors (see Table 1).

Type of objective

The type of objective, whether quantitative or qualitative, likely affects salespeople's relational behaviors. Most sales contest objectives are set in quantitative terms, such as an increase in sales. However, firms might also include qualitative objectives, such as customer satisfaction, as a means to limit the negative effects of sales contests [START_REF] Sharma | Customer Satisfaction-based Incentive Systems: Some Managerial and Salesperson Considerations[END_REF]. [START_REF] Murphy | In Pursuit of Short-Term Goals: Anticipating the Unintended Consequences of Using Special Incentives to Motivate the Sales Force[END_REF] shows that safeguards and ethical rules can help maintain the customer relationship, as an alternative to a qualitative sales framework.

Competition format

Most firms use individual competition formats because individual performance is easier to measure; however, group formats outperform individual when the strength of social ties among the group members matters [START_REF] Lim | When do Group Incentives for Salespeople Work?[END_REF] and when cooperation and mutual assistance is important [START_REF] Drago | Competition and Cooperation in the Workplace[END_REF]. In a collective format, salespeople's customer orientation is more likely to be preserved [START_REF] Poujol | The Impact of Contest on Salespeople's Customer Orientation: An Application of Tournament Theory[END_REF], supporting relationship-based selling. It would be interesting to examine the impact of contests that combine individual and collective formats on relational behaviors.

Budget and number of winners

A sales contest might set several goal levels, depending on the type of budget (open or closed) and number of winners. Contestants care about the value of the prizes they receive, as well as their contest outcomes relative to other contestants. Changing the proportion of winners in a contest can alter the reference points contestants use to make these social comparisons. Some researchers note that closed competitions can induce sabotage of other salespeople, even if they are on the same sales team [START_REF] Drago | Competition and Cooperation in the Workplace[END_REF]. As cooperation become increasingly important in sales organizations, [START_REF] Lim | Designing Sales Contests: Does the Prize Structure Matter?[END_REF] note the importance of a sales contest prize structure that does not endanger cooperation within the sales force.

Rewards

Determining rewards is a crucial question in designing a contest [START_REF] Murphy | Increasing Sales Contest Effectiveness: The Determinants of Positive Attitude toward Sales Contests[END_REF][START_REF] Lim | Designing Sales Contests: Does the Prize Structure Matter?[END_REF]. Companies often use a mixture of rewards, combining bonuses, gifts, gift vouchers, or travel vouchers; vary them for different levels of the competition; or offer participants a choice. Noncash prizes, in which the perceived differences in monetary value are less precise, do not lead to a reduction in effort when compared to cash prizes [START_REF] Lim | When do Group Incentives for Salespeople Work?[END_REF], though inside salespeople prefer cash [START_REF] Hollet-Haudebert | Understanding Inside Salespeople's Preferences for Contest Design Attributes and Rewards[END_REF].

Duration

The length of a sales contest also provokes debate with regard to motivation versus relationship quality. Generally, it should be rather short, to keep salespeople motivated throughout the entire process but too short may result in the fridge effect, overstocking, and forward buying [START_REF] Murphy | In Pursuit of Short-Term Goals: Anticipating the Unintended Consequences of Using Special Incentives to Motivate the Sales Force[END_REF]. Structuring sales contests with different deadlines could limit the disadvantages of excessively short competitions though, by rewarding salespeople according to the final results [START_REF] Poujol | Caractéristiques d'un challenge de vente et adhésion des commerciaux: Quelques recommandations[END_REF].

Effects of sales contests on salespeople's relational behaviors

In sum, sales contest design can affect salespeople's behaviors and attitudes toward their clients. For example, they might feel encouraged to adopt more aggressive sales techniques, overstock clients, or express less patience in their efforts to sell more [START_REF] Sharma | The Impact of Customer Satisfaction Based Incentive Systems on Salespeople's Customer Service Response: An Empirical Study[END_REF]. [START_REF] Murphy | In Pursuit of Short-Term Goals: Anticipating the Unintended Consequences of Using Special Incentives to Motivate the Sales Force[END_REF]) classifies salespeople's problematic behaviors, citing (1) decreased mutual assistance and information sharing among sales representatives, (2) reckless risk taking, (3) negligence of other work, (4) emphasis on the contest product to the detriment of other products, and

(5) forward selling and overstocks as the most dangerous of problematic behaviors, especially for customer relationship quality. When they engage in such behaviors, salespeople are unlikely to listen to their customers and offer appropriate products because the rewards accrue only for the sale of a focal product.

Studies related to the impact of sales contests on relational behaviors of salespeople remain limited. No research addresses their effect on customer listening behaviors, despite the potential influence on salespeople's customer orientation and adaptability [START_REF] Pelham | An Exploratory Study of the Influence of Sales Training Content and Salesperson Evaluation on Salesperson Adaptive Selling, Customer Orientation, Listening and Consulting Behaviors[END_REF]. Yet in spite of the importance of listening to adaptive selling and customer relationship building, the effects of common sales management tools such as sales contests on customer listening have not been examined.

Customer listening is a key antecedent of customer trust, satisfaction, and loyalty. As [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF] note, clients who think salespeople are listening to find appropriate solutions are more likely to trust, to feel more satisfied and to continue in the relationship. Therefore, this study focuses on the customer listening, an important relational component performed by salespeople during their interactions with clients, both during and outside of sales contest periods.

Customer listening

Scholars have taken several approaches to customer listening. Some have focused on individual factors that determine listening while others have portrayed listening as a function of techniques, an application of which yields various levels of listening quality. Still others have focused on a process of listening consisting of several steps.

Individual components

Salesperson conditions strongly determine customer listening, including patience, concentration [START_REF] Alessandra | Non-Manipulative Selling[END_REF], emotional intelligence, human warmth, and open-mindedness. Empathy may be the main determinant, though, of effective listening [START_REF] Lewis | Listening in Organizational Environments[END_REF][START_REF] Castleberry | Effective Interpersonal Listening and Personal Selling[END_REF][START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF]. Effective listening requires 'perceiving a person's precise internal framework of reference and with its components and emotional significance in order to feel them as if we were that person but without ever forgetting the "as if"' (Brunel and Martiny 2004, 477). Empathy takes three forms: thought (verbal dimension), emotion (emotional dimension), and action (interactional synchrony) [START_REF] Brunel | Les conceptions de l'empathie avant, pendant et après Rogers[END_REF]. Both [START_REF] Covey | The Seven Habits of Highly Effective People[END_REF] and [START_REF] Tracy | Stop Talking … and Start Asking Questions[END_REF] integrate empathy to extend the concept of empathetic listening and [START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF] consider empathy as an active form of listening. That is, Active Empathetic Listening (AEL) consists of receiving verbal and non-verbal messages and evaluating the meaning by putting the self into someone else's shoes. 'It's a form of listening practiced by salespeople in which traditional active listening is combined with empathy to achieve higher form of listening' (Drollinger, Comer, and Warrington 2006, 162).

Levels and techniques

Comer and [START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF] propose a graduated listening model based on the degrees to which listeners (e.g. salespeople) seek knowledge about the message provider (e.g. customer). In line with [START_REF] Alessandra | Non-Manipulative Selling[END_REF], they distinguish marginal, evaluative, and active listening, and then integrate AEL. Thus, a salesperson moving up this hierarchy would first hear without listening, then listen to the literal meaning of the words but without perceiving any non-verbal dimensions, and finally process the message fully and respond to continue the discussion. The addition of empathy ensures the salesperson's strong involvement in listening, such that he or she grows closer to the client to learn about and understand him. Thus, empathy makes listening stronger, because the listener sincerely desires to be totally involved in what is being said [START_REF] Covey | The Seven Habits of Highly Effective People[END_REF][START_REF] Tracy | Stop Talking … and Start Asking Questions[END_REF].

To engage in customer listening, salespeople might adopt two main techniques: passive or active. Passive listening implies being silent; active listening suggests an effort to give meaning to messages received and signaling this search for understanding to the message sender. By questioning and reformulating the message, active listeners reveal their desire to understand the exact meaning of verbal and non-verbal messages. Thus it promotes exchanges that provide information clarity and express interest in verbal and non-verbal components of interpersonal communications. Active listening generates a better effectiveness in the interaction between a seller and a customer [START_REF] Brooks | The Power of Active Listening[END_REF].

Process

Process-oriented researchers have largely adopted a definition of listening as 'the cognitive process of actively sensing, interpreting, evaluating, and responding to the verbal and non-verbal messages of present or potential customers' (Castleberry and Shepherd 1993, 36). Listening as a process includes several steps creating an ordered construct of listening [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF]. These steps are Sensing, Interpreting, Evaluating, and Responding [START_REF] Steil | Effective Listening: Key to Your Success[END_REF], or SIER, as illustrated in Figure 1.

The first step, Sensing, involves taking in all messages (verbal, non-verbal and paraverbal, or tone, silence, laughs, etc.) coming from the sender. The second step, Interpreting, implies an active participation from the receiver to find the meaning of what is sent and said by the sender. In the third step, Evaluating, the listener exploits knowledge to convert what was perceived into information, sorting by importance or relevance. The fourth step, Responding, is the formulation of a response that translates the understanding of the sent message.

The SIER process was integrated into the sales literature in the 1990s [START_REF] Castleberry | Effective Interpersonal Listening and Personal Selling[END_REF] Figure 1. The listening process (SIER) [START_REF] Steil | Effective Listening: Key to Your Success[END_REF]. [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF][START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF]. Process-based researchers defined listening in sales as 'the cognitive process of actively sensing, interpreting, evaluating and responding to the verbal and non-verbal messages of present or potential customers' (Castleberry and Shepherd 1993, 36). Some studies combine the middle two steps into a single step called Evaluating [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF] or Processing [START_REF] Castleberry | Effective Interpersonal Listening and Personal Selling[END_REF][START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF]. This step, Processing, implies an assignment of meaning to incoming messages and includes questions intended to add meaning through directing responses. Consistently though, a listening process starts with Sensing, continues with Processing, and finishes with Responding: the formulation of an answer that expresses the cognitive mechanisms in place, producing a balance between the messages emitted and the messages received, whether verbal or non-verbal.

Adding empathy to the process produces the concept of AEL [START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF]. However, empathy is also separate from the process, considered by some as an antecedent to effective listening [START_REF] Steil | Effective Listening: Key to Your Success[END_REF][START_REF] Aggarwal | Salesperson Empathy and Listening: Impact on Relationship Outcomes[END_REF].

Customer listening by salespeople has been studied in diverse business sectors (e.g. automobile, [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF]industrial, Comer and Drollinger 1999;pharmaceutical, Limbu and Javachandran 2012;financial, Bergeron and Laroche 2009;insurance, Goby and Lewis 2000). These studies on customer listening focus on faceto-face sales, even though sales communications also occur through mediated and multiple channels, such as the telephone. Telesales creates a unique context, in that the message senders and receivers cannot see each other and cannot rely as much on non-verbal elements (e.g. eye contact, body language, mimics, and facial expressions) as they might in face-to-face interactions. Rather, messages are verbal and paraverbal; non-verbal elements of the interpersonal communication are not available. In call centers, salespeople handle calls continuously, with limited time and in noisy conditions, so the discussion context is very different from a face-to-face setting.

Listening is a predictor variable in several studies, predicting client satisfaction, customer trust [START_REF] Ramsey | Listening to Your Customers: The Impact of Perceived Salesperson Listening Behavior[END_REF], sales performance [START_REF] Castleberry | Effective Interpersonal Listening and Personal Selling[END_REF], and relational sales [START_REF] Drollinger | Salesperson's Listening Ability as an Antecedent to Relationship Selling[END_REF]. Customer listening also serves as a dependent variable in studies of personal and professional sales determinants [START_REF] Roman | The Influence of the Compensation System and Personal Variables on a Salesperson's Effective Listening Behavior[END_REF], though such studies generally ignore the impact of a sales contest. As a dependent variable, customer listening might depend on parameters linked to the execution of sales tasks, in the presence or absence of sales contests.

Generally, researchers separate the techniques of listening from the processes of listening, though they can be associated [START_REF] Koehl | L'influence des bruits sur la qualité de l'écoute du téléconseiller d'un centre d'appels[END_REF][START_REF] Koehl | Theories and Practices of Customer Listening: An Exploratory Qualitative Study with Banking Telesales Agents in France[END_REF]. Passive and active listening are techniques of listening associated with the Sensing and Processing steps. When sensing, the receiver does not speak and is taking in all stimuli. When processing, the receiver searches for the meaning that is implied in the exchange by questioning, reformulating, and applying knowledge. In a telesales context, considering the exchange is only oral between telesales agent and customers without the ability to observe non-verbals and considering the working conditions, the process of listening is applied in a short time and concentrated on verbal and paraverbal components. These particularities and the results of the literature review lead us to retain a listening process with three steps: Hearing, Processing, and Responding.

Hypotheses

Prior research on commission-based compensation plans indicates a potential negative effect on customer listening [START_REF] Aiello | Electronic Performance Monitoring and Social Context: Impact on Productivity and Stress[END_REF][START_REF] Roman | The Influence of the Compensation System and Personal Variables on a Salesperson's Effective Listening Behavior[END_REF]. The compensation plan influences selling techniques and financial motivations [START_REF] Kurland | Sales Agents and Clients: Ethics, Incentives and a Modified Theory of Planned Behavior[END_REF]. [START_REF] Honeycutt | Determinants of Ethical Behavior: A Study of Auto Salespeople[END_REF] suggest that sellers adopt selling approaches with an 'open, without pressure' approach if compensation is not primarily commission-based; conversely, salespeople adopt a 'closed, with pressure' approach when on commission-based plans. A contest, with the opportunity for additional cash earnings, prizes, or recognition based on sales volume, may orient sellers toward less listening. Contests may promote a more directive sales approach at the detriment of listening, as the sales rep seeks to maximize sales for the sake of winning. Further, since salespeople or telesales agents are frequently constrained to meet quotas or goals for phone calls in a given time period, contests focused on quantitative objectives may disrupt the quality of listening.

Where, though, is this disruption greatest? We expect, based on the perspective of [START_REF] Honeycutt | Determinants of Ethical Behavior: A Study of Auto Salespeople[END_REF], that a contest will likely yield behaviors that are more closed, with pressure. If so, we would expect that the presence of a contest would result in fewer practices of good customer listening. That is, a contest may increase self-serving motivation to the detriment of the listening. The listening process based on the steps Hearing, Processing, and Responding may also be negatively affected during a period of sales contest conducting to formulate the following research hypotheses: H1: A sales contest has a negative impact on Hearing. H2: A sales contest has a negative impact on Processing.

H3: A sales contest has a negative impact on Responding.

Empirical study

Study context

This natural field experiment involves observing listening practices during the treatment of calls made by 90 telesales agents. These telesales agents work in an inbound call center that manages the customer portfolio of a specialized mobile phone provider. Their profile presents the following characteristics: more than half are between 20 and 25 years old, are male (56.5%), and have less than 18 months of experience. One-third has a high school diploma, onethird a bachelor's degree and one-third has some graduate school education. Temporary telesales agents are not included in the study.

The telesales agents consider each inbound call a sales opportunity. They are not limited to scripts, which grant them more freedom in their conversations with clients. Each telesales agent has received training on a sales process that includes listening. Management recommends 10 minutes as a time limit per call in order to discover how customers use their mobile phone so as to propose new options and up selling adapted to their needs. Calls with poor reception or high levels of ambient noise were eliminated from study so as not to misinterpret observations. This study, conducted over several months, spans periods marked by a sales contest and those without any contest, so it is possible to evaluate the agents' customer listening practices across both the presence and the absence of a sales contest.

The sales contest was designed by experts in incentive operations (see Appendix 1 for details). The objective was to increase sales of options and upselling. The sales of options and upselling were assigned points and those points could be converted into prizes (e.g. high-fidelity equipment), depending on the number of points accumulated. Prizes were awarded after 90 days, while commission is paid monthly. Commissions are paid on individual sales results and quality measures and the relative weight of commission varies somewhat by sales agent. The contest had both an individual and collective (teambased) format.

Participation in the contest was not mandatory and those agents who chose to participate are entirely autonomous as they recorded themselves by signing up online through a dedicated intranet space. An internal communication plan explained the sales contest and attempted to motivate telesales agents to participate. Specific eligibility rules required accomplishment of a minimum threshold of selling of options and upselling; failure to reach the threshold eliminated the telesales agent from the contest. Furthermore, controls and sanctions sought to prevent fraud, and management conducted customer satisfaction calls after a random sample of sales to ensure that satisfaction levels were maintained. Clearly stated rules established conditions for elimination or sanctions.

The results were communicated via monitors visible to all agents and via their email. Since sales can be canceled by customers, contest results were not made final until 90 days after the contest ended, ensuring that only real sales would be considered.

Evaluation of customer listening practices

To evaluate the telesales agents' customer listening practices, a researcher worked closely with the call center's quality department and gained real-time access to the agents' telephone lines. The assessments of calls included two groups of telesales agents randomly selected: sales contest participants and non-participants (between-subjects). The dependent variable is individual listening behavior. The evaluations of the participants (within-subjects) spanned both the contest period and a non-contest period, which featured no sales incentive programs (e.g. no temporary 'flash sales' created by managers to offer one-off sales incentives), to enhance the reliability of the results.

For this telesales context, which differs from face-toface sales settings, existing measures of customer listening, such as the AEL scale [START_REF] Comer | Active Empathetic Listening and Selling Success: A Conceptual Framework[END_REF] or the ILPS (Interpersonal Listening in Personal Selling) scale [START_REF] Castleberry | Effective Interpersonal Listening in the Personal Selling Environment: Conceptualization, Measurement, and Nomological Validity[END_REF] are not appropriate. Instead, a preliminary exploratory study was conducted to evaluate customer listening in telephonemediated relationships. The results of this exploratory qualitative study completing an extensive literature review allows to find potential items for the evaluation of customer listening [START_REF] Koehl | L'influence des bruits sur la qualité de l'écoute du téléconseiller d'un centre d'appels[END_REF][START_REF] Koehl | Theories and Practices of Customer Listening: An Exploratory Qualitative Study with Banking Telesales Agents in France[END_REF]. Then, telesales experts working in a different call center reviewed the items. Through this collaboration, theories about listening were integrated with earlier observations to formulate items suitable within the context of telesales and a process of listening. The formulated items have been then submitted to telesales experts of the selected call center who were responsible for ensuring service quality in the treatment of the calls. The items have been analyzed both independently by practitioner experts, and then collaboratively with the researcher to assess listening practices and process employed on sales phone calls. Results were compared and conclusions formulated to avoid biases in evaluation; differences were noted and precisions in formulations were given. For each formulated item, details of evaluation were specified in an index form. For example, for the item 'formulates clear questions', weighted elements are the degree of precision to validate an understanding via questions such as: 'do I understand correctly? It is not clear for me, can you give me more information, more precise please? "For the item" expresses his/her empathy', weighted elements are: 'yes, I see; yes, I understand; I agree with you'. After tests of evaluations on calls and convergent notation between telesales experts and researcher, all inbound calls selected for the study were evaluated by the researcher who worked in the conditions of a real professional laboratory. The researcher, equipped with a headset, evaluated only calls by a phoning connection without knowing and seeing telesales agents and by being focused only on selected listening items that characterize the treatment of an inbound call avoiding all risks of dispersion and external perturbations.

The evaluations of practices of customer listening included a pretest on 150 inbound calls. The items were analyzed with a principal component analysis with a varimax rotation, revealing four listening dimensions that explain 72.44% of the total variance, 45.12% through active listening, and 10.75% through adaptive listening. The four dimensions reflect four listening techniques: passive listening, active listening, as well as two new dimensions: adaptive listening and assertive listening (Cronbach's alpha > .9, Bartlett test = .000, Kaiser-Mayer-Olkin (KMO) index close to .9). These four listening techniques are confirmed with a control of reliability on 320 calls (Cronbach's alpha > 9, Bartlett test = .000, KMO index close to .9). They have a direct link with the steps of the listening process retained for the study including the three steps Hearing, Processing, and Responding. This operationalization of the listening process is then used to evaluate inbound calls.

For telesales agents, passive listening consists of listening to messages sent by clients over the telephone line while being welcoming and receptive (evaluated items: identifies the mobile status of the call, doesn't repeat the customer, is receptive). In this respect, the agent does not ask clients to repeat the reasons for their calls or specify their needs. This dimension matches the Hearing step of the listening process. With active listening (evaluated items: uses responses to continue the dialog, formulates clear questions, formulates questions to continue the dialog, uses objections to continue the dialog, expresses his (her) empathy, is in the relationship, reformulates essential points), telesales agents ask questions, express empathy and reformulate or confirm key points. The agent is focused on the conversation and seeks to extend it, which parallels a Processing step in the listening process. Both adaptive listening (evaluated items: gives an adaptive response to customer's needs, gives an adaptive response to customer's questions, gives a response in cohesion with the objectives of the mission) and assertive listening (evaluated items: answers without pressure by being affirmative, respects the customer in his (her) words, doesn't formulate rapid conclusions, masters his (her) emotions) represent responses, based on the previous steps, in line with the Responding step of the listening process. Telesales agents position themselves as specialized sales advisors and become involved in what the client is saying, which promotes balanced communication. Whereas adaptive listening implies that the agent adapts to the messages expressed by the client, assertive listening indicates that the agent actively expresses statements about one's own professional skills, while still respecting the client and without coming to a hasty conclusion.

Once the four dimensions of listening were identified, the researcher evaluated inbound calls in real time on a 7-point scale from very bad (1 point) to excellent (7 points). The evaluation of listening began from the beginning of a connection with a customer to the conclusion of the call. Specialized software allows for the following of any connection with customers. When a customer contacts the call center, the call is identified and the listening practice is evaluated for the telesales agent taking the call. The calls were randomly selected and monitored at three different points throughout the days and at different hours. Each telesales agent is followed with an identification number to assure anonymity. This approach avoids asymmetries in abilities that might influence outcomes. The age, gender, and position (level and type) of those studied were consistent with the profile of the employees within the call center and the individual factors did not significantly influence any of the variables of interest. Evaluations of calls during the sales contest included telesales agents who voluntarily agreed to participate, who work in the frontline service area, and who were eligible according to the rules of eligibility (see Appendix 1).

Results

The data related to the evaluations of the telesales agents' customer listening practices underwent an analysis of variance and means comparisons, conducted with SPSS software. The results pertain to both within-and betweensubject findings regarding telesales agents. First, the between-subject data related to 250 call evaluations reveal significant results for passive (p = .04) and active (p = .00) listening, but not for adaptive or assertive listening (Table 2). The test of the mean comparison of factorial scores indicates the impact of the sales contest was negative on passive and active listening. That is, telesales agents who participated in the sales contest exhibited less passive and active listening than telesales agents did outside the contest period. This negative impact in turn should affect the Hearing and Processing steps of the listening process and result in poorer quality customer listening during a sales contest period validating H1 and H2.

The within-subjects results include 162 call evaluations; the impact again is significant for passive (p = .04) and active (p = .07) listening but not for adaptive or assertive listening techniques of listening or Responding part of listening (Table 3). This test of the comparison of means of the factorial scores shows a negative impact of the sales contest on passive and active listening. That is, telesales agents who participated in the sales contest exhibited worse customer listening when answering incoming telephone calls during the sales contest period but better customer listening outside of the contest period. This negative impact similarly affected the Hearing and Processing steps of the listening process and led to poorer quality customer listening.

Thus, the study results confirm the original research proposal: a sales contest has a negative impact on customer listening, and as hypothesized, several steps of the listening process are negatively affected. The negative results during contest periods are particularly significant for passive and active listening implying the steps Hearing and Processing of the listening process. Adaptive and assertive listening also suffer poorer results during contest periods but the differences are not statistically significant to confirm the H3. Thus, the negative effect may be considered partial and not global, because it is only significant for passive and active listening implying the Hearing and Processing steps of the listening process. Only H1 and H2 are supported; H3 is not (Figure 2). Overall though, the quality of the customer listening declines when a sales contest is in effect, according to both the within-and between-subject findings.

Discussion

This study advances understanding of listening and contests in several ways. First, the influence of a contest is not uniform across all forms of listening. Second, some forms of listening are surprisingly relatively unimportant when considering short-term performance outcomes. These findings require some reconsideration of adaptive selling and the role of contests in managing salesperson behavior and performance.

This study provides evidence that listening is negatively influenced by a sales contest; however, the observed negative impacts of the sales contest on the Responding dimension of listening (adaptive and assertive listening) are not significant. Thus, even if a telesales agent fails to hear the client (Hearing dimension) or becomes less involved in the conversation (Processing dimension), he/ she still can offer a response that is coherent with sales objectives and advising the client.

Two possible explanations for the contest's effects on listening can be made. First, the contest focused salespeople to seek specific outcomes; in an effort to accomplish these outcomes, salespeople gave short shrift to passive and active listening. Given the stronger sales outcomes for those participating in the sales contest, the shortcut did not damage short-term sales outputs, suggesting that these aspects of listening may not be important. [START_REF] Pryor | Salesperson Listening in the Extended Sales Relationship: An Exploration of Cognitive, Affective, and Temporal Dimensions[END_REF] note that customers look for expressions of empathy, which may increase the importance of Responding (adaptive and assertive listening techniques). Future research should consider whether Hearing and Processing dimensions of listening (passive and active listening) are important to customer satisfaction with the call experience and other possible outcomes, and whether there is some minimum threshold that signals sufficient interest on the part of the salesperson.

Further, a combination of salesperson knowledge and sales process simplicity may contribute to the salesperson's ability to shortcut the process. Thus, in an effort to achieve higher levels of sales, salespeople may have made strategic decisions as to what could be dropped from the call without hurting chances for the sale. While this study controlled for experience and the environment involved fairly simple selling, a more complex setting may lead to findings that shortcuts cannot be taken, no matter the nature of incentives. Thus, research regarding control systems should examine contextual factors that may influence the relative effectiveness of the systems. The second explanation for these findings is that the specific modalities of the sales contest examined in this study limited the effects of the contest on the Responding dimension of listening (adaptive and assertive listening). These modalities aimed to protect the customer relationship quality for the focal firm, but the sales contest still hindered Hearing and Processing steps (passive and active customer listening). This negative impact might not be global, in that the sales contest did not affect adaptive or assertive listening significantly, but a lack of passive and active listening over time may significantly disrupt relationship quality, particularly in relation to empathy and signals that the sales agent does not want to understand the customer's messages. Poor quality active listening also implies poorer understanding of the client and its needs, which may lead to lower relational quality and threaten the continuation of the relationship.

The results also might reflect the rules and guidelines associated with this particular sales contest. Boosting sales was the primary goal, but rules included constraints on sales persistence. The controls, set at different levels, assign sanctions if salespeople force sales or achieve incoherent (and possibly fraudulent or harmful) results. This qualitative approach aims to safeguard against sales misconduct potentially explaining why sales contest did not affect adaptive and assertive listening techniques significantly. That is, a failure to engage in the Responding dimension of listening might imply sales misconduct and invoke sanctions for the salesperson. The telesales agents in this study thus may have avoided pressuring clients to prevent being punished.

During the sales contest, telesales agents asked the client to repeat more often, a sign of reduced Hearing. Exploration of the client's needs and expectations through questions or restatements (active listening) is also not as frequent. This result may reflect the salesperson's stronger orientation toward a presentation of new offers in line with the sales contest incentives, as well as an increase in speaking relative to listening. However, because adaptive and assertive listening are not significantly negatively affected, the sales contest seemingly does not create a sufficiently strong anti-relational orientation that the sales conversations end abruptly. The customer relationship is not entirely unbalanced, and forced sales due to pressure do not appear to occur, which likely is due to the qualitative rules of the contest, as noted previously.

Effective listening is an important element in the adaptive selling process [START_REF] Spiro | Adaptive Selling: Conceptualization, Measurement and Nomological Validity[END_REF][START_REF] Castleberry | Effective Interpersonal Listening and Personal Selling[END_REF][START_REF] Shepherd | Linking Effective Listening with Salesperson Performance: An Exploratory Investigation[END_REF] and this study, with the identification of adaptive listening, offers additional insight into how listening can be important for adaptive selling [START_REF] Koehl | A State of the Art of Adaptive Selling[END_REF]. Adaptive listening allows sellers to signal deeper empathy and a customer focus to contribute to the application of adaptive selling. The salesperson searches for understanding that enable customer-specific solutions and with the practice of assertive listening, he/she is situated in the step Responding without applying pressure and without jumping to conclusions. Thus, an important contribution is the distinction of adaptive and assertive listening. Customers rely on listening behaviors as signals of empathy [START_REF] Pryor | Salesperson Listening in the Extended Sales Relationship: An Exploration of Cognitive, Affective, and Temporal Dimensions[END_REF]. As such, an interesting validation study would include the customer perspective of adaptive and assertive listening. If these are truly distinctive forms of listening behavior, they should reflect differentially in customer responses. For example, future research could consider whether these are additive or multiplicative in influencing customer perceptions of empathy.

This study further suggests that adaptive selling supporting a customer orientation can be managed through outcome controls (the qualitative rules of the contest). Contests, as one form of controls (cf. [START_REF] Miao | The Interactive Effect of Sales Control Systems on Salesperson Performance: A Job Demands-Resources Perspective[END_REF], have been shown here to influence listening in potentially dangerous ways but not at the expense of short-term outcomes. Thus, this study helps to integrate several theoretical approaches to understanding salesperson performance. Indeed, the contest creates modifications in working conditions of sellers. Therefore the particularities of the context of selling generated by the presence or absence of a contest appeal consideration. 'The nature of the selling situation' (Weitz, Sujan, and Sujan 1986) that is included in the concept of adaptive selling can also find a new delimitation with the consideration of the working conditions of sellers who are implied or not in incentives operations such as contests.

These findings suggest that adaptive selling supporting a customer orientation can be managed through outcome controls [START_REF] Anderson | Perspectives on Behavior-based versus Outcome-based Sales Force Control Systems[END_REF], in this case the qualitative rules of the contest. Thus, this study helps to integrate several theoretical approaches to understanding salesperson performance.

Managerial implications

At a managerial level, the study results should raise awareness of how sales contests alter salespeople's listening practices to the possible detriment of global customer listening quality. To avoid the potential customer relationship damage, managers should set qualitative objectives in addition to quantitative goals and determine limits for the various modalities of the sales contest. Specific rules associated with the sales contest might help ensure customer listening; a call processing framework also might remind sales agents of their ethical responsibilities and the need to ensure the high quality of their relationships with clients.

With regard to designing the sales contest modalities, the choice of rewards should be consistent with the company's regular compensation plan. When pay incentives focus on productivity, salespeople seek to achieve their sales objectives without listening [START_REF] Aiello | Electronic Performance Monitoring and Social Context: Impact on Productivity and Stress[END_REF], such as through sales approaches that are closed or pressuring, especially if they are paid by commission [START_REF] Honeycutt | Determinants of Ethical Behavior: A Study of Auto Salespeople[END_REF]. In this study, the rewards were not financial, which might explain the partial negative impact of the sales contest. This finding indicates that managers must choose sales contest rewards carefully and is to be considered with the results of the works of [START_REF] Lim | Designing Sales Contests: Does the Prize Structure Matter?[END_REF].

Because the results show negative effects of a sales contest for only two dimensions of listening (passive and active), corresponding to Hearing and Processing steps of listening process, a sales contest is not inherently antirelational; instead, it creates a temporary microclimate of the cultural and ethical climate of each company. As Bergadaà (2005) explains, well-established ethical rules can help companies ensure that their employees act in conformity with their corporate culture. A sales contest, implemented in a particular professional context with unique rules, seemingly should be able to induce specific objectives that are both ethical and relational. In implementing sales contests, managers should therefore adopt principles for high quality customer relationships and select qualitative measures, such as those used to assess customer listening. In this sense, a contest can constitute a management tool for developing better quality contacts even when also trying to increase sales.

The results of this study further indicate that when telesales agents work without scripts, there is diversity in call management. Training, then, becomes important, not only in what to say but also in how to listen.

Limitations

This study includes several limitations that suggest pathways for further research, in addition to those opportunities noted earlier. All calls came from one firm with one set of work conditions. A cross-sectional sample would complement this field experiment by confirming or refuting our initial results and scale development.

In this study, we can infer that Hearing and Processing dimensions of customer listening (passive and active listening) may not be that important to sales outcomes since sales performance improved for those participating in the contest. Future work should consider other outcomes, such as customer satisfaction with the sales call experience and effects on longer term relational outcomes. Further, direct testing of the effects of listening types on sales outcomes should be conducted. For example, questions such as whether a minimal threshold of passive and active listening must be met or whether complexity of the setting influences the importance of listening should be examined.

Sales contest scholars should also consider how sales contests with varying modalities (e.g. duration types of rewards, etc.) influences customer listening. For managers seeking to protect customer relationship quality yet apply sales contests, further research should also clarify the effects of safeguards or ethical conduct rules. An interesting question would be whether a contest could not only be used to meet sales goals but also to contribute to the organization's ethical culture or to role clarity by addressing specific salesperson behaviors such as listening. Research into contest modality and effects on customer listening and other specific behaviors could help immensely with questions of contest impact.

Further research into other explanatory factors (covariates), such as the company's and manager's customer orientation, could enrich this research, to the extent some of the variance might be linked to these variables. Additional research also could investigate in greater depth which variables contribute to explain a telesales agent's listening habits. The term call center covers a wide range of situations both organizationally and in terms of the business function. Moreover, it would be productive to consider other characteristics of call centers; for example, the nature of the calls (incoming or outgoing), the type of selling and marketing activity, and the business sector (B-to-B or B-to-C). This great diversity of call centers is one of the variables that potentially can influence salespeople's listening. In addition, the evolution towards contact centers reflecting the diversity of contact media and format suggest that listening may not be limited to aural sensory of verbals, but should perhaps include text. Customer listening researchers should consider crossover into digital listening in social media and email.

Conclusion

This field experiment led to the identification of additional dimensions in customer listening, as well as the influence of a sales contest on listening. The negative impacts on two listening dimensions, Hearing and Processing, imply poorer listening quality when salespeople are participating in a sales contest in a call center setting. The results highlight the need to consider customer listening as a key dependent variable in sales studies and particularly as a dependent variable on the conditions of incentives on sales. Beyond serving as a tool to motivate salespeople and boost sales, a sales contest also affects salespeople's relational behaviors; thus, continued research must consider the complementarity between customer listening and the management of customer information through the use of mediated channels. These results indicate that customer listening research is still maturing, and significant opportunity lies ahead in this area of research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Figure 2 .

 2 Figure 2. Results of the impact of a sales contest on customer listening.

Table 1 .

 1 Sales contest characteristics and salespeople's relational behaviors.

	Sales contest
	characteristics	Modalities	Effect on Relationships	Authors and year
	Nature of the	Quantitative or	Qualitative objectives would limit the negative effects of	Sharma (1997)
	objective	qualitative	sales contests
	Competition	Individual or collective Collective format is more conducive to relationship-	Poujol and Tanner (2010); Lim
	format		based selling and stronger internal (team)	and Chen (2014)
			relationships
	Budget	Open or closed	A ranking can induce sabotage of other salespeople	Drago and Turnbull (1991);
	Number of winners Small of medium	High proportion of winners is better if social loss	Lim (2010)
			aversion is strong
	Reward	Monetary or not,	Prize values should be unique and rank ordered;	Lim, Ahearne, and Ham (2009);
		structure of the	monetary reward is preferred but no study on the	Hollet-Haudebert et al.(2015)
		reward	impact of reward on CRM
	Duration	Short, medium or long	Short-term duration negatively impacts interactions with	Garrett and Gopalakrishna
		term	customers	(2010)
	Frequency	Low or high	Low frequency is better for customer orientation of	Poujol and Tanner (2010)
			salespeople

Table 2 .

 2 Impact of a sales contest on customer listening (between-subject).

		Hearing	Processing	Responding
		Passive listening	Active listening	Adaptive listening	Assertive listening
	F (1; 161)	4.019	14.478	0.466	1.879
	p	0.046	0.000	0.496	0.172
	Comparison of means of factorial scores
	No contest	0.093	0.174	0.032	0.094
	Sales contest	-0.169	-0.315	-0.058	-0.116

Table 3 .

 3 Impact of a sales contest on customer listening (within-subject).

		Hearing	Processing	Responding
		Passive listening	Active listening	Adaptive listening	Assertive listening
	F (1; 249)	4.151	7.583	1.594	.342
	p	0.043	0.007	0.209	0.559
	Comparison of means of factorial scores
	No contest	0.175	0.234	0.109	0.050
	Sales contest	-0.143	-0.192	-0.089	-0.041

Criterion Description of each criterion

Nature of the objective Quantitative objective: to increase sales of product options and upselling on several segments of customers Competition format Individual and collective format: Individual telesales agents and teams of telesales agents (minimum of six telesales agents and maximum of thirteen telesales agents with a single team leader) Budget and Ranking

. Closed budget: selective ranking with a pre-determined number of winners . Ranking depended on total points . In the case of a tie between agents, the agent who closed the most long term sales was the winner . In the case of tie between teams, the team which had the smaller number of telesales agents eliminated for failing to meet the minimum sales limit was the winner Rewards Extrinsic: Material prizes: Hi-Fi equipment Length and Period Four weeks

The end of one year on two months: November and December Frequency Low: No other incentive plan during this period Internal communication

. before the sales contest: at the end of October, an email was sent announcing contest; informative and motivational spots on the sales contest via televisions on the phoning platform . during the sales contest: display of messages with results via video monitors on the phoning platform and by email . at the end of the sales contest: display of a provisory ranking on the dedicated intranet space before dissemination of the final ranking three months after (in respect with the time of sustainability of sales)

Modalities of participation

. Participation is voluntary . To be eligible for prizes, the participant had to reach a minimum sales level for options and of upselling . Transformation of each sale into points based on size and type of sale, as well as whether the customer was new or current

Controls and sanctions

. Regular analysis of results

. Wave of control with outbound calls towards customers after the treatment of the inbound calls . Daily, weekly controls on sales . Telesales agents ruled ineligible (eliminated) if high rate of cancelations, decrease in customer satisfaction (based on wave of control), or evidence of high pressure (based on wave of control) . Restitution of Hi-Fi prizes if identification of fraud after diffusion of results and attribution of prizes


Mohammed Nafi
email: mohammed.nafi@cnam.fr

Samia Bouzefrane
email: samia.bouzefrane@cnam.fr

Mawloud Omar
email: mawloud.omar@univ-eiffel.fr

Efficient and Lightweight Polynomial-based Key Management Scheme for Dynamic Networks

Keywords: Polynomial, Key management, Lightweight

Wireless sensor networks and Internet of Things (IoT) are part of dynamic networks as new nodes can join while existing members can leave the system at any time. These networks mainly suffer from severe resource constraints like energy, storage and computation, which makes securing communications between nodes a real challenge. Several key establishment protocols have been proposed in the literature. Some of them are based on symmetric polynomials. However, the latter solutions have some limitations, such as the resilience to node capture attacks as well as the storage and computation overheads that are high for constrained nodes. In this paper, we propose a lightweight polynomial-based key management scheme for dynamic networks. The proposed scheme allows nodes to be able to establish secure communications between them, and ensures dynamism by supporting node addition and deletion after the setup phase. It also resists to node capture attack. The performance evaluation shows that our scheme reduces both the storage and computation overheads when compared to other related polynomial-based protocols.

Introduction

A dynamic network can be defined as a distributed system whose topology changes continuously over time, where new nodes join the network while existing members leave it at any time. Ad hoc networks, wireless sensor networks and the Internet of Things (IoT) are some examples of dynamic systems since they allow addition and removal of nodes after the deployment phase. These networks are widely used in many application domains such as military, patient and environmental monitoring, agriculture, smart cities and smart homes, Supported by General Directorate for Scientific Research and Technological Development, Ministry of Higher Education and Scientific Research (DGRSDT), Algeria.

etc. The nodes mainly share a wireless communication channel through which they exchange messages. However, this medium is vulnerable to various types of attacks if it is not secured. Securing such a channel should involve the use of cryptographic keys. However, managing these keys is a complex process, due to essentially high resource constraints of some nodes.

Several key predistribution approaches have been proposed in the literature for dynamic networks, especially for wireless sensor networks. Some of them rely on the use of polynomials [START_REF] Blundo | Perfectly-secure key distribution for dynamic conferences[END_REF][START_REF] Liu | Establishing pairwise keys in distributed sensor networks[END_REF][START_REF] Fanian | An efficient symmetric polynomial-based key establishment protocol for wireless sensor networks[END_REF][START_REF] Zhang | Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme[END_REF][START_REF] Kumar | Polynomial based non-interactive session key computation protocol for secure communication in dynamic groups[END_REF], which allows two nodes to establish a pairwise key between them. In these schemes, nodes generally share a common symmetric t-degree polynomial so that any pair of nodes is able to compute the same pairwise key by evaluating the polynomial using as input the identifier of the other node. For instance, Blundo et al. [START_REF] Blundo | Perfectly-secure key distribution for dynamic conferences[END_REF] introduced a multi-variate t-degree polynomial-based group key predistribution scheme.

The main drawback of these polynomial-based schemes is that when an adversary physically captures a node, he or she may be able to access its memory and therefore get the shared polynomial. As a result, the adversary could calculate the pairwise key between any pair of nodes by evaluating the polynomial at the identifiers of those nodes. In other words, compromising one node could also affect other communication links between non-captured nodes.

In this paper, we propose a lightweight polynomial-based key management scheme for dynamic constrained networks. Our scheme mainly aims to address the aforementioned limitations of existing polynomial-based schemes. In fact, instead of using the identical polynomial to compute all the secret keys, nodes do not share the same polynomial in our scheme. Accordingly, compromising a node affects the links it shares with its neighbors, but has a little influence on those between non-compromised nodes. In addition, the proposed scheme significantly reduces the storage and computation overheads on the constrained node side. The main features of the proposed scheme are highlighted below:

-Our solution is more resistant to node capture attacks since nodes do not share the same polynomial. In fact, compromising a node has a little influence on the links between two non-captured nodes; -It reduces the memory overhead. In fact, each node has to store (d + 1) coefficients of a bivariate polynomial instead of (t + 1) shares, where d is the number of neighbors; -It reduces the computation cost. Indeed, to be able to establish a pairwise key, one node must evaluate only two adequate terms of its polynomial, rather than all the terms of a t-degree polynomial as in the other schemes; -It enables dynamism following the addition and deletion of nodes. In other words, nodes can join or leave the network at any time. These operations have only impact on the nodes that are in the neighborhood.

The rest of this paper is organized as follows. Section 2 discusses some existing polynomial-based key establishment solutions. Our proposed polynomial-based key management scheme is described in detail in Section 3. Its performance evaluation is presented in Section 4. Section 5 concludes this paper and gives some future research directions.

Related work

Various mathematical key predistribution schemes have been proposed in the literature for wireless sensor networks. Some schemes make use of matrices [START_REF] Nafi | Matrix-based key management scheme for IoT networks[END_REF][START_REF] Blom | An optimal class of symmetric key generation systems[END_REF][START_REF] Du | A key management scheme for wireless sensor networks using deployment knowledge[END_REF] while others rely on polynomials [START_REF] Blundo | Perfectly-secure key distribution for dynamic conferences[END_REF][START_REF] Liu | Establishing pairwise keys in distributed sensor networks[END_REF][START_REF] Fanian | An efficient symmetric polynomial-based key establishment protocol for wireless sensor networks[END_REF][START_REF] Zhang | Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme[END_REF][START_REF] Kumar | Polynomial based non-interactive session key computation protocol for secure communication in dynamic groups[END_REF]. In this section, we discuss some schemes belonging to the latter category.

Blundo et al. [START_REF] Blundo | Perfectly-secure key distribution for dynamic conferences[END_REF] proposed a non-interactive multi-variate t-degree polynomialbased group key predistribution scheme. This scheme uses symmetric polynomial of m variables, where m is the group size. When the group has only two members (m = 2), this scheme degenerates into a symmetric bivariate polynomial-based scheme. To obtain the same pairwise key, a pair of nodes evaluates the polynomial at the identifier of the other. This scheme is t-secure and no communication is required between nodes during the key establishment process. However, each node must store (t + 1) (m-1) coefficients, and evaluate all the polynomial's terms when computing a secret key. In addition, compromising more than t nodes leads to the compromise of the entire network.

To improve the resilience to node capture attacks, D. Liu et al. [START_REF] Liu | Establishing pairwise keys in distributed sensor networks[END_REF] proposed a key predistribution framework based on a pool of polynomials. In this scheme, a set of random bivariate polynomials is used instead of a single polynomial. A subset of polynomials' shares is assigned to each sensor. A pair of nodes establishes a direct key if they have a common polynomial shares. Otherwise, they compute a path key by relying on intermediate nodes. This scheme is more resilient to compromising attacks. However, the storage overhead is increased when compared to the previous scheme.

A. Fanian, et al. [START_REF] Fanian | An efficient symmetric polynomial-based key establishment protocol for wireless sensor networks[END_REF] introduced a key establishment protocol, called SKEP, based on symmetric t-degree (k + 1)-variate polynomials, where k is a credential. In their scheme, the network is first divided into separate virtual hexagonal cells. Then, each cell receives a group of sensors, which share the same symmetric tdegree bivariate polynomial. Two members of the same cell establish a direct key, while a pair of sensors from different groups computes an indirect key. In SKEP, each sensor stores the polynomial shares of two distinct t-degree polynomials. This scheme is scalable and resilient to node capture attack. However, the storage overhead remains high when compared to some other related protocols.

J. Zhang et al. [START_REF] Zhang | Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme[END_REF] proposed a key predistribution scheme for wireless sensor networks that combines both random and polynomial-based key predistribution schemes. Each sensor is assigned with g t-degree polynomials picked from a pool of m elements along with their identifiers. The nodes are also given s keys with their identifiers. Two neighbors can compute a pairwise key if they share the same polynomial or key, or at least a key of one node is derived from the polynomial shares of the other node. This scheme has better resilience to node capture attacks. However, it introduces some additional storage and computation overheads.

A polynomial-based session key establishment scheme in dynamic groups, called NISKC, is presented by V. Kumar et al. in [5]. This scheme uses a multivariate t-degree polynomial, where the number of variables is equal to the group size m. So, each node can compute the session key by putting its private value in the polynomial. This scheme is efficient in terms of communication overhead, and allows node addition and deletion after the deployment phase. However, the storage and the computation costs are still high.

Authors in [START_REF] Staddon | Self-healing key distribution with revocation[END_REF] were the first to introduce a non-interactive group key distribution scheme with revocation that has the self-healing property. The key idea is that only active members have the ability to recover the missed session keys by combining the key shares received before and after the lost. These key shares are complementary to each other. The scheme allows users to be able to establish a group key in an unreliable environment. In addition, it enables users to join or leave the group as well. However, this scheme requires high storage and communication overheads. Moreover, Blundo et al. in [START_REF] Blundo | Design of Self-Healing Key Distribution Schemes[END_REF] presented an attack against the first construction of this scheme.

Another efficient session key distribution scheme for unreliable wireless sensor networks was proposed in [START_REF] Mukhopadhyay | Improved Self-Healing Key Distribution with Revocation in Wireless Sensor Network[END_REF]. The scheme has also the self-healing and revocation features as the previous one. Each user stores a t-degree polynomial with the initial or current session identifier. From a broadcast message, each non-revoked user is able to compute the current session key, which is in turn used to recover the self-healing keys. The scheme reduces both the storage and the communication overheads. Moreover, authors mentioned that their scheme also ensures forward and backward secrecy since users that join the network at a subsequent session ignore the initial session identifier. However, authors in [START_REF] Daza | Flaws in some self-healing key distribution schemes with revocation[END_REF] showed that this scheme does not really resist against forward and backward attacks.

Note that in most existing polynomial-based key establishment protocols, nodes generally share the same t-degree polynomial. Consequently, if more than t nodes are captured, the whole network will be compromised. Moreover, the storage and computation overheads are considerable for constrained nodes. In this paper, we propose a polynomial-based scheme where nodes do not necessarily share the same polynomial, which makes it more resilient to node capture attacks and efficient in terms of storage and computation overheads.

ELiPKMS: The proposed scheme

In this section, we present our proposed scheme, called ELiPKMS (Efficient and Lightweight Polynomial-based Key Management Scheme), which allows nodes to establish secure links in their neighborhood. ELiPKMS consists of six phases, namely the setup, neighbor discovery, key generation, node addition, node deletion and key refresh phases, which are described in detail in the following. The notation used in this paper is summarized in Table 1.

Setup

The trusted server generates a bivariate symmetric 2n-degree polynomial over the finite field F (q), where n represents the number of nodes in the network during the deployment phase. The form of the obtained polynomial, let's say f (x, y) = n i=1 a i x i y i , and the initial network key K n are then preloaded into the memory of each node before its deployment.

Neighbor discovery

Once the deployment is done, each node proceeds to discover other nodes that are within its communication range. To do that, each node i generates a random secret value, denoted a i , and then broadcasts a Hello message encrypted with the initial network key K n . This message contains the sender's identifier and its generated secret value. Each node i holds a neighbor table t i wherein it stores its identifier along with its secret value as well as those received from its adjacent nodes (j, a j ), with j ∈ t i . At the end of this discovery phase, each node i orders its neighbor table in ascending order of the identifiers. Afterwards, it uses the polynomial's form to generate its own bivariate d i -degree polynomial according to its direct neighbors, where d i = 2 * M ax(j), with j ∈ t i , as described in the equation Eq.1.

f i (x, y) = a j x j y j , with j ∈ t i .

(

) 1
where a j is the secret value of the node j.

Key establishment

Two kinds of keys are used: direct and indirect keys that are established as in the following.

Direct key When a pair of neighbors i and j want to securely communicate with each other, they first compute a common pairwise key K ij by evaluating only the two appropriate terms of their respective polynomials as follows: f i (i, j) = a i i i j i + a j i j j j and f j (j, i) = a j j j i j + a i j i i i , where a i and a j are the secret values of the nodes i and j respectively. As a result, both nodes obtain the same symmetric secret key as shown in Eq.2.

K ij = f i (i, j) = f j (j, i) = K ji (2)
Path (indirect) key A node i that needs to communicate in a secure way with a non-neighbor node j, tries to establish a key path via intermediate nodes. To do so, the node i requests assistance from its direct neighbors by sending them a request encrypted with the appropriate direct keys. This request contains the identifier of the sender i as well as its secret value a i and the identifier of the other node j. A neighbor k that receives such a request, decrypts it with the adequate direct key K ki , and then checks its neighbor table to determine whether or not the node j belongs to its neighbors. If the verification is not successful, the message will simply be ignored. Otherwise, the intermediate node checks the freshness of that message by comparing the received secret value a i with the one already stored in its neighbor table. If the verification fails, the node discards the message. Otherwise, the intermediate node computes a path key K ij for both nodes i and j in the same way as it is performed between two neighbors by evaluating the corresponding terms of its polynomial. After that, this key is sent back to each of the two nodes within a response message encrypted with the appropriate pairwise keys. Upon receiving the previous message from the intermediate node, both nodes i and j decrypt it and store the path key K ij . The latter nodes are then able to use this indirect key in order to establish secure communication between them.

Example Let's consider a network initially deployed with three nodes, as shown in Figure 1. After deployment, the nodes 1, 2 and 3 generate, for instance, the secret values a 1 = 11, a 2 = 22 and a 3 = 33 respectively. At the end of the discovery phase, each node generates its own polynomial as follows:

As the node 1 has two neighbors, hence its polynomial contains three terms:

f 1 (x, y) = a 1 x 1 y 1 + a 2 x 2 y 2 + a 3 x 3 y 3 .
As the degree of the node 2 is equal to one, hence its polynomial has two terms:

f 2 (x, y) = a 1 x 1 y 1 + a 2 x 2 y 2 .
The degree of the node 3 is also equal to one, hence its polynomial has two terms too:

f 3 (x, y) = a 1 x 1 y 1 + a 3 x 3 y 3 .
The nodes 1 and 2 compute the direct pairwise key by evaluating the appropriate two terms of their polynomials as follows: Node 1 computes the key

K 12 = f 1 (1, 2) = a 1 x 1 y 1 + a 2 x 2 y 2 = 11 * 1 1 * 2 1 + 22 * 1 2 * 2 2 = 110. Node 2 computes the keyK 21 = f 2 (2, 1) = a 2 x 2 y 2 + a 1 x 1 y 1 = 22 * 2 2 * 1 2 + 11 * 2 1 * 1 1 = 110.
In the same way, both nodes 1 and 3 compute their common direct key. Node 1 computes the key

K 13 = f 1 (1, 3) = a 1 x 1 y 1 + a 3 x 3 y 3 = 11 * 1 1 * 3 1 + 33 * 1 3 * 3 3 = 924. Node 3 computes the key K 31 = f 3 (3, 1) = a 3 x 3 y 3 + a 1 x 1 y 1 = 33 * 3 3 * 1 3 + 11 * 3 1 * 1 1 = 924.
Finally, each pair of neighbors obtains the same direct pairwise key. As a result, they establish a secure channel and can communicate securely. Furthermore, when the node 2 needs to communicate securely with the node 3 that is not inside of its radio range, it solicits the help of the intermediate node 1. The latter computes for them a path key as follows:

K 23 = f 1 (2, 3) = a 2 x 2 y 2 + a 3 x 3 y 3 = 22 * 2 2 * 3 2 + 33 * 2 3 * 3 3 = 7920.

Node addition

Before deployment, a new node has to request the trusted server to obtain the present network key K n as well as the current polynomial's form used by the network members. After that, the new node generates a secret value, let's say a n , and broadcasts a Join message that contains especially its identifier with that secret value. The Join message is encrypted using the network key K n . A neighbor that receives this message uses the network key to decrypt it and updates its neighbor table by inserting the identifier and the secret value of the new node. Afterwards, it adds to its polynomial a term that corresponds to that new node, and responds back with an acknowledgment Ack message, which contains its identifier along with its secret value, let's say a i . When receiving the Ack messages, the new node updates its neighbor table in turn, and constructs its polynomial. Finally, both the current member and the new node are able to compute a common key by evaluating the adequate two terms of their polynomials as follows:

k in = f i (i, n) = f n (n, i) = a i x i y i + a n x n y n = a n x n y n + a i x i y i .
It is important to note that at each node addition, the polynomials of all neighbors of the new node are increased by one term.

Example Let's assume that the new node 4 joins the network as depicted in Figure 2. During the setup phase, the node 4 is preloaded with the network key K n and the form of the current polynomial before its deployment in the area of interest. Just after deploying it, that node generates a secret, let's say a 4 = 44, then broadcasts in its neighborhood a Join message encrypted with the network key. The nodes 1 and 2 are neighbors of the node 4, so they receive that message. These nodes will then decrypt it and update their neighbor table by adding the ID and secret value of the new node 4. After that, they respond back with an Ack message containing their IDs along with their generated secret values. Upon receiving the Ack messages, the node 4 decrypts them and adds the IDs as well as these secrets a 1 and a 2 to its neighbor table.

The nodes 1 and 4 respectively and separately compute their direct pairwise key as follows:

K 14 = f 1 (1, 4) = a 1 1 1 4 1 + a 4 1 4 4 4 = 11 * 1 * 4 + 44 * 1 * 256 = 11308. K 41 = f 4 (4, 1) = a 4 4 4 1 4 + a 1 4 1 1 1 = 44 * 256 * 1 + 11 * 4 * 1 = 11308.
Note that nodes 1 and 4 obtain the same pairwise key:

K 14 = K 41 .
The nodes 2 and 4 respectively and separately compute their direct pairwise key as follows:

K 24 = f 2 (2, 4) = a 2 2 2 4 2 + a 4 2 4 4 4 = 22 * 4 * 16 + 44 * 16 * 256 = 181632. K 42 = f 4 (4, 2) = a 4 4 4 2 4 + a 2 4 2 2 2 = 44 * 256 * 16 + 22 * 16 * 4 = 181632.
Note that nodes 2 and 4 also get the same direct pairwise key: K 24 = K 42 . Moreover, the nodes 3 and 4 are also able to secure their communications by using the path key K 34 , which can be computed by the intermediate node 1.

Node deletion

When a node is compromised or leaves the network with its willingness, all its neighboring nodes carry out the following operations:

-Update their neighbor tables by removing the entry corresponding to the leaving node; -Delete the polynomial's term of that node; -Erase the pairwise key they share with that node.

It is important to notice that at each node deletion, the polynomials of all nodes adjacent to the outgoing node, are decreased by one term.

Key refresh

To counter some kinds of security attacks, the network key and the established pairwise keys must be periodically refreshed. To do so, the server node regularly generates a new network key K n , and chooses a completely different symmetric polynomial's form. The latter are then transmitted to the network members in a secure way. Upon receiving these new security parameters, all members replace the old network key and use the received polynomial's form to generate their new symmetric bivariate polynomials. After that, they use the obtained polynomials to compute the new pairwise keys and erase the old keys afterwards.

Performance evaluation and comparison

To evaluate the performance of the proposed scheme, we focus primarily on efficiency metrics such as the storage and computation overheads. We compare ELiPKMS with the polynomial-based protocols [START_REF] Fanian | An efficient symmetric polynomial-based key establishment protocol for wireless sensor networks[END_REF], [START_REF] Zhang | Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme[END_REF], and [START_REF] Kumar | Polynomial based non-interactive session key computation protocol for secure communication in dynamic groups[END_REF] described in Section 2. The simulations are developed using MATLAB environment [14]. The nodes are randomly deployed in a square area of 100 m 2 . The network size ranges from 10 to 100 nodes. Each node is equipped with a communication radio with a range equal to 10 m. We assume that the number of polynomials picked from the polynomial pool is equal to one (g = 1) in [START_REF] Zhang | Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme[END_REF], while the t-degree polynomial used in [START_REF] Kumar | Polynomial based non-interactive session key computation protocol for secure communication in dynamic groups[END_REF] is bivariate. Note that these two last parameters are set to their minimum values. The simulation parameters are summarized in Table 2.

Storage overhead

In the simulations, we are interested in the storage space occupied by both polynomials shares and their identifiers (IDs). We assume that these coefficients and IDs are chosen from two pools of 100 elements each. Moreover, the polynomial degree is set to 10 in the other schemes. Figure 3 shows the storage overhead in function of the network size. We can clearly see that the memory space required to store polynomials' shares and IDs increases with increasing the number of nodes in the network. However, ELiPKMS requires less storage cost when compared to the other schemes. This is because in ELiPKMS, each node needs to store (d + 1) polynomial's coefficients, whereas in the other schemes, each node must save at least (t + 1) polynomial's shares. Accordingly, the total storage space is considerably reduced in our scheme.

Computation overhead

In the experiments, we focused on the computation cost in terms of the number of polynomials' terms evaluated when each node establishes one pairwise key. Figure 4 illustrates the computation overhead depending on the network size.

From the figure, we note that ELiPKMS largely outperforms the other schemes. This is due to the fact that unlike the most existing polynomial-based schemes where a node evaluates all the terms of the same t-degree polynomial in order to compute one pairwise key, in our scheme, each node needs to evaluate only two adequate terms of its polynomial. In this way, ELiPKMS significantly reduces the computation cost at the constrained node side.

Comparison

A fair comparison between our scheme and the related works discussed in Section 2 is shown in Table 3. This comparison is made according to the storage and computation overheads. As mentioned before, the storage cost is estimated based on the memory space occupied by polynomials' coefficients and identifications, while the computation overhead is related to the number of polynomials' terms evaluated during the pairwise key establishment. According to [START_REF] Harn | Predistribution Scheme for Establishing Group Keys in Wireless Sensor Networks[END_REF], each node has to store (t + 1) (m-1) coefficients for a t-degree polynomial of m variables.

We have assumed that the polynomial shares are chosen from the same finite field F (q), and the identifications are selected from F (q ), with q and q are two large numbers. The value s represents the number of communication sessions considered in [START_REF] Staddon | Self-healing key distribution with revocation[END_REF]. (t + 1) (m-1) * log q (t + 1) (m-1) [START_REF] Liu | Establishing pairwise keys in distributed sensor networks[END_REF] s (t + 1) * log q + s * log q (t + 1) [START_REF] Fanian | An efficient symmetric polynomial-based key establishment protocol for wireless sensor networks[END_REF] 2(t + 1) * log q (t + 1) [START_REF] Zhang | Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme[END_REF] g(t + 1) * log q + g * log q ≤ (t + 1) [START_REF] Kumar | Polynomial based non-interactive session key computation protocol for secure communication in dynamic groups[END_REF] (t + 1) (m-1) * log q (t + 1) (m-1) [START_REF] Staddon | Self-healing key distribution with revocation[END_REF] s * (t + 1) * log q (t + 1) [START_REF] Mukhopadhyay | Improved Self-Healing Key Distribution with Revocation in Wireless Sensor Network[END_REF] (t + 1) * log q ≥ (t + 1) ELiPKMS (d + 1) * log q 2

Conclusion

In this paper, we have proposed an efficient and lightweight polynomial-based key management scheme in dynamic networks with high resource constraints. Compared to existing polynomial-based protocols, our proposed scheme ELiP-KMS significantly reduces the amount of key material stored in the memory of each node as well as the computation overhead since the number of multiplications and additions operations required to generate a pairwise key is reduced.

As future work, we first intend to assess the energy consumption of the proposed scheme during communication and computation operations, and then expand the security analysis by including a formal verification using AVISPA tool [START_REF] Armando | The AVISPA tool for the automated validation of internet security protocols and applications[END_REF], in order to check whether this scheme resists well to some known attacks and satisfies the secrecy, integrity and authentication properties.

Fig. 1 .

 1 Fig. 1. Network with three nodes

Fig. 2 .

 2 Fig. 2. Node addition

Fig. 3 .

 3 Fig. 3. Storage overhead vs. network size (t=10, g=1)

Fig. 4 .

 4 Fig. 4. Computation overhead vs. network size (t=10, m=2)

Table 1 .

 1 Notation

	Notation Description
	x, y	Variables of the polynomial
	i, j	Identifiers of nodes i and j
	ai	Secret value of node i (coefficient of the polynomial)
	F (q)	Finite or Galois field of q elements
	Kn	Network key
	Kij	Pairwise key shared between nodes i and j
	ti	Neighbor table of the node i
	di	Degree of the polynomial of the node i
	d	Degree of the node (number of neighbors)

Table 2 .

 2 Simulation parameters

	Parameter	Value
	Network area	100 m × 100 m
	Radio range	10 m
	Network size	varies from 10 to 100 nodes
	F (q), F (q )	Finite fields of 100 elements each
	Polynomials' degree	t = 10
	Number of selected polynomials g = 1
	Number of polynomials' variables m = 2

Table 3 .

 3 Comparison

	Scheme Storage	Computation
	[1]