Purpose – The purpose of this paper is to examine whether and how family ownership enhances or damages firm value. Design/methodology/approach – The paper studies a sample of Canadian companies listed on the Toronto Stock Exchange (TSX) between 1999 and 2007 and apply multivariate regression with firm value as a dependent variable. The paper measures firm value as Tobin ' s Q and ROA based either on net income or EBITDA. The independent variables include family firm dummy and ownership percentage. Findings – It is found that control-enhancing mechanisms which are often employed by family companies add value to companies. Furthermore, it is found that agency conflicts between ownership and management are less costly than those between majority and minority shareholders, suggesting that family ownership helps resolve the agency conflicts between ownership and management and in turn enhances firm value. Finally, it is found that family companies with founders as CEOs outperform those with descendants as CEOs. Research limitations/implications – The paper studies Canadian family firms; as such, the sample size is not relatively large. Nonetheless, the results should be generalized as Canada is one of the largest markets in the world and have high integration with the rest of the world. Practical implications – The results suggest investors should invest in family ownership firms. Originality/value – The paper shows whether firm ownership increases firm value and the determinant of family firm value.

This paper examines a manufacturer's supply management strategies for mitigating yield risk in a complex dynamic supply chain. Two strategies can be adopted for the manufacturer: backup and reliability improvement. Consumers may select to leave (instant consumers) or wait (delaying consumers) when they confront the manufacturer's insufficient inventory. Utilizing the method of multi-agent modeling, a manufacturer and a supplier are modeled as the intelligent agents with the reinforcement learning behavior. The study shows that: 1) when the number of instant consumers is small, reliability improvement strategy should be selected; otherwise, the manufacturer should adopt a backup strategy; 2) only when mean yield is large enough, reliability improvement strategy is the optimal choice; and 3) if yield uncertainty is small, the manufacturer should choose reliability improvement strategy; otherwise, it is suitable to use a backup strategy. In addition, when the main supplier can determine its own wholesale price, it is found that: 1) when the mean yield is small, a lower wholesale price should be designed for the main supplier, to induce higher order quantity under backup strategy; and 2) the impact of yield uncertainty on the manufacturer's supply management strategy can be changed by the main supplier's adaptive pricing behavior. INDEX TERMS Consumer behavior, multi-agent modeling, supply chain management, yield risk.

Whether to use an information sharing mechanism is investigated in a dynamic supply chain, where one manufacturer, one carrier, and one retailer are faced with uncertain yield, demand, and lead time during multiple periods. Each member is modeled as an adaptive agent based on multiagent technique, and their decisions can be adjusted timely to adapt to external environment. There are two choices for the whole supply chain to deal with uncertain risks: information sharing (IS) or no information sharing (NS). Under strategy IS, the information about market demand and the retailer’s inventory can be shared within the supply chain. For each strategy, the effects of yield, demand, and lead time uncertainties on costs of the supply chain and channel members are studied. It is found that (i) it is rewarding for the upstream manufacturer to use a retailer’s shared information under uncertain yield or demand; (ii) however, information sharing (IS) strategy sometimes should be abandoned for other members and the whole supply chain; (iii) counterintuitively, the increase of transportation time uncertainty benefits the retailer.

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This paper examines pricing strategies for two adaptive retailers competing on two products in the presence of complex consumer behavior, where consumers own heterogeneous product and store valuations and the number of potential consumers is random. Each retailer can choose one from two pricing strategies: the uniform pricing format (offering the same price for two products) or the differentiated pricing format (offering different prices). Utilizing agent-based model (each retailer is modeled as an autonomous agent with the reinforcement learning behavior), we find that: (i) the differentiated pricing format is not always the optimal choice; (ii) when the uncertainty of one product/store valuation is a little larger than that of the rival, both retailers should adopt uniform pricing. Besides, when wholesale price contract is endogenous, we find that supplier’s pricing behavior can change the impact of the fixed cost on the pricing strategy.